Model backlog/Evaluation/196-Tweet-Evaluation-5Fold-roBERTa seq_len64 hidden 08 warmup.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.6"},"colab":{"name":"196-Tweet-Train-5Fold-roBERTa seq_len64 hidden 08 warmup.ipynb","provenance":[],"collapsed_sections":[]},"accelerator":"GPU"},"cells":[{"cell_type":"code","metadata":{"id":"rOXNne0OoLTd","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":105},"outputId":"605d63c1-1c77-4b30-d9b7-ce383616d1bb","executionInfo":{"status":"ok","timestamp":1590493439545,"user_tz":180,"elapsed":12487,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["!pip --quiet install transformers\n","!pip --quiet install tokenizers"],"execution_count":1,"outputs":[{"output_type":"stream","text":["\u001b[K     |████████████████████████████████| 665kB 4.8MB/s \n","\u001b[K     |████████████████████████████████| 890kB 63.0MB/s \n","\u001b[K     |████████████████████████████████| 3.8MB 56.0MB/s \n","\u001b[K     |████████████████████████████████| 1.1MB 59.4MB/s \n","\u001b[?25h  Building wheel for sacremoses (setup.py) ... \u001b[?25l\u001b[?25hdone\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"htKChfMHoYRb","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":125},"outputId":"b1a586f3-38aa-4fa8-8609-83bfe25a9bab","executionInfo":{"status":"ok","timestamp":1590493461762,"user_tz":180,"elapsed":34692,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["from google.colab import drive\n","drive.mount('/content/drive')"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n","\n","Enter your authorization code:\n","··········\n","Mounted at /content/drive\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"xtDZkoyzod_S","colab_type":"code","colab":{}},"source":["!cp -r '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Scripts/.' ."],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"38KKgQn7owCr","colab_type":"code","colab":{}},"source":["COLAB_BASE_PATH = '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/'\n","MODEL_BASE_PATH = COLAB_BASE_PATH + 'Models/Files/196-roBERTa_base/'"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"MOE8CNSAnvq-","colab_type":"text"},"source":["## Dependencies"]},{"cell_type":"code","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_kg_hide-input":true,"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","id":"x48gxo3vnvrA","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":72},"outputId":"44ddcbc8-5f17-4aad-8f88-59b8c0464f7d","executionInfo":{"status":"ok","timestamp":1590493470993,"user_tz":180,"elapsed":43906,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["import json, glob, warnings\n","from tweet_utility_scripts import *\n","from tweet_utility_preprocess_roberta_scripts_aux import *\n","from transformers import TFRobertaModel, RobertaConfig\n","from tokenizers import ByteLevelBPETokenizer\n","from tensorflow.keras import layers\n","from tensorflow.keras.models import Model\n","\n","SEED = 0\n","seed_everything(SEED)\n","warnings.filterwarnings(\"ignore\")\n","pd.set_option('max_colwidth', 120)"],"execution_count":5,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n","  import pandas.util.testing as tm\n"],"name":"stderr"}]},{"cell_type":"markdown","metadata":{"id":"6HW0GQzPnvrF","colab_type":"text"},"source":["# Load data"]},{"cell_type":"code","metadata":{"id":"jS858zlQNNCs","colab_type":"code","colab":{}},"source":["# Unzip files\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_64/fold_1.tar.gz'\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_64/fold_2.tar.gz'\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_64/fold_3.tar.gz'\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_64/fold_4.tar.gz'\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_64/fold_5.tar.gz'"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_kg_hide-input":true,"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","id":"hVhA98wenvrG","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":551},"outputId":"d29876e6-d236-46f4-9019-a113b1b5d325","executionInfo":{"status":"ok","timestamp":1590493480833,"user_tz":180,"elapsed":53735,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["database_base_path = COLAB_BASE_PATH + 'Data/complete_64/'\n","k_fold = pd.read_csv(database_base_path + '5-fold.csv')\n","display(k_fold.head())"],"execution_count":7,"outputs":[{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>textID</th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>sentiment</th>\n","      <th>jaccard</th>\n","      <th>text_len</th>\n","      <th>text_wordCnt</th>\n","      <th>text_tokenCnt</th>\n","      <th>selected_text_len</th>\n","      <th>selected_text_wordCnt</th>\n","      <th>selected_text_tokenCnt</th>\n","      <th>fold_1</th>\n","      <th>fold_2</th>\n","      <th>fold_3</th>\n","      <th>fold_4</th>\n","      <th>fold_5</th>\n","      <th>imputed</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>cb774db0d1</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>35</td>\n","      <td>7</td>\n","      <td>10</td>\n","      <td>35</td>\n","      <td>7</td>\n","      <td>10</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>validation</td>\n","      <td>train</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>549e992a42</td>\n","      <td>sooo sad i will miss you here in san diego!!!</td>\n","      <td>sooo sad</td>\n","      <td>negative</td>\n","      <td>0.200000</td>\n","      <td>45</td>\n","      <td>10</td>\n","      <td>13</td>\n","      <td>8</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>validation</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>088c60f138</td>\n","      <td>my boss is bullying me...</td>\n","      <td>bullying me</td>\n","      <td>negative</td>\n","      <td>0.166667</td>\n","      <td>25</td>\n","      <td>5</td>\n","      <td>6</td>\n","      <td>11</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>train</td>\n","      <td>validation</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>9642c003ef</td>\n","      <td>what interview! leave me alone</td>\n","      <td>leave me alone</td>\n","      <td>negative</td>\n","      <td>0.600000</td>\n","      <td>30</td>\n","      <td>5</td>\n","      <td>6</td>\n","      <td>14</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>train</td>\n","      <td>validation</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>358bd9e861</td>\n","      <td>sons of ****, why couldn`t they put them on the releases we already bought</td>\n","      <td>sons of ****,</td>\n","      <td>negative</td>\n","      <td>0.214286</td>\n","      <td>74</td>\n","      <td>14</td>\n","      <td>17</td>\n","      <td>13</td>\n","      <td>3</td>\n","      <td>4</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>validation</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>False</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["       textID  ... imputed\n","0  cb774db0d1  ...   False\n","1  549e992a42  ...   False\n","2  088c60f138  ...   False\n","3  9642c003ef  ...   False\n","4  358bd9e861  ...   False\n","\n","[5 rows x 17 columns]"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"b0bUTMPynvrM","colab_type":"text"},"source":["# Model parameters"]},{"cell_type":"code","metadata":{"id":"Paexn4ywnvrM","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":176},"outputId":"f57bd3da-ae52-4cd4-c33f-78cf0c863ed5","executionInfo":{"status":"ok","timestamp":1590493482061,"user_tz":180,"elapsed":54955,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["vocab_path = COLAB_BASE_PATH + 'qa-transformers/roberta/roberta-base-vocab.json'\n","merges_path = COLAB_BASE_PATH + 'qa-transformers/roberta/roberta-base-merges.txt'\n","base_path = COLAB_BASE_PATH + 'qa-transformers/roberta/'\n","\n","with open(MODEL_BASE_PATH + 'config.json') as json_file:\n","     config = json.load(json_file)\n","\n","config"],"execution_count":8,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'BATCH_SIZE': 32,\n"," 'EPOCHS': 7,\n"," 'ES_PATIENCE': 3,\n"," 'LEARNING_RATE': 3e-05,\n"," 'MAX_LEN': 64,\n"," 'N_FOLDS': 5,\n"," 'base_model_path': '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/qa-transformers/roberta/roberta-base-tf_model.h5',\n"," 'config_path': '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/qa-transformers/roberta/roberta-base-config.json',\n"," 'question_size': 4}"]},"metadata":{"tags":[]},"execution_count":8}]},{"cell_type":"markdown","metadata":{"id":"D_8F5nxDnvrW","colab_type":"text"},"source":["# Tokenizer"]},{"cell_type":"code","metadata":{"_kg_hide-output":true,"id":"6qeQlxrDnvrX","colab_type":"code","colab":{}},"source":["tokenizer = ByteLevelBPETokenizer(vocab_file=vocab_path, merges_file=merges_path, \n","                                  lowercase=True, add_prefix_space=True)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"3aHwZDF9nvrR","colab_type":"text"},"source":["# Model"]},{"cell_type":"code","metadata":{"id":"7gIO5wkQnvrS","colab_type":"code","colab":{}},"source":["module_config = RobertaConfig.from_pretrained(config['config_path'], output_hidden_states=True)\n","\n","def model_fn(MAX_LEN):\n","    input_ids = layers.Input(shape=(MAX_LEN,), dtype=tf.int32, name='input_ids')\n","    attention_mask = layers.Input(shape=(MAX_LEN,), dtype=tf.int32, name='attention_mask')\n","    \n","    base_model = TFRobertaModel.from_pretrained(config['base_model_path'], config=module_config, name=\"base_model\")\n","    _, _, hidden_states = base_model({'input_ids': input_ids, 'attention_mask': attention_mask})\n","    \n","    h08 = hidden_states[-5]\n","    \n","    x = layers.Dropout(.1)(h08)\n","    \n","    x_start = layers.Dense(1)(x)\n","    x_start = layers.Flatten()(x_start)\n","    y_start = layers.Activation('softmax', name='y_start')(x_start)\n","    \n","    x_end = layers.Dense(1)(x)\n","    x_end = layers.Flatten()(x_end)\n","    y_end = layers.Activation('softmax', name='y_end')(x_end)\n","\n","    model = Model(inputs=[input_ids, attention_mask], outputs=[y_start, y_end])\n","    \n","    return model"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"jy24FlCgnvrj","colab_type":"text"},"source":["# Make predictions"]},{"cell_type":"code","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"id":"RU2sa648nvrj","colab_type":"code","colab":{}},"source":["k_fold_best = k_fold.copy()\n","\n","for n_fold in range(config['N_FOLDS']):\n","    n_fold +=1\n","\n","    # Load data                               \n","    base_data_path = 'fold_%d/' % (n_fold)\n","    x_train = np.load(base_data_path + 'x_train.npy')\n","    y_train = np.load(base_data_path + 'y_train.npy')\n","    x_valid = np.load(base_data_path + 'x_valid.npy')\n","    y_valid = np.load(base_data_path + 'y_valid.npy')\n","\n","    # Load model\n","    model_path = 'model_fold_%d.h5' % (n_fold)\n","    model = model_fn(config['MAX_LEN'])\n","    \n","    # Make predictions\n","    model.load_weights(MODEL_BASE_PATH + model_path)\n","    predict_eval_df(k_fold_best, model, x_train, x_valid, get_test_dataset, decode, n_fold, tokenizer, config, config['question_size'])"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"xxbg-_R_p2dE","colab_type":"text"},"source":["# Model evaluation"]},{"cell_type":"code","metadata":{"id":"KgsapEFup3zY","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":302},"cellView":"form","outputId":"3ac7e2fe-3024-4ca2-a881-1f679a021191","executionInfo":{"status":"ok","timestamp":1590496287156,"user_tz":180,"elapsed":4766,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","display(evaluate_model_kfold(k_fold_best, config['N_FOLDS']).style.applymap(color_map))"],"execution_count":37,"outputs":[{"output_type":"display_data","data":{"text/html":["<style  type=\"text/css\" >\n","    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col0 {\n","            color:  black;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col1 {\n","            color:  black;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col2 {\n","            color:  red;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col3 {\n","            color:  black;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col4 {\n","            color:  black;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col5 {\n","            color:  black;\n","        }    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#T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col7 {\n","            color:  black;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col8 {\n","            color:  black;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col9 {\n","            color:  black;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col10 {\n","            color:  black;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col11 {\n","            color:  black;\n","        }    #T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col12 {\n","            color:  black;\n","        }</style><table id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Train</th>        <th class=\"col_heading level0 col1\" >Valid</th>        <th class=\"col_heading level0 col2\" >Var</th>        <th class=\"col_heading level0 col3\" >Train_fold_1</th>        <th class=\"col_heading level0 col4\" >Valid_fold_1</th>        <th class=\"col_heading level0 col5\" >Train_fold_2</th>        <th class=\"col_heading level0 col6\" >Valid_fold_2</th>        <th class=\"col_heading level0 col7\" >Train_fold_3</th>        <th class=\"col_heading level0 col8\" >Valid_fold_3</th>        <th class=\"col_heading level0 col9\" >Train_fold_4</th>        <th class=\"col_heading level0 col10\" >Valid_fold_4</th>        <th class=\"col_heading level0 col11\" >Train_fold_5</th>        <th class=\"col_heading level0 col12\" >Valid_fold_5</th>    </tr>    <tr>        <th class=\"index_name level0\" >Metric/Jaccard</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n","                <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Overall</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col0\" class=\"data row0 col0\" >0.758274</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col1\" class=\"data row0 col1\" >0.705592</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col2\" class=\"data row0 col2\" >0.052682</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.772490</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0.705490</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col5\" class=\"data row0 col5\" >0.767459</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col6\" class=\"data row0 col6\" >0.703057</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.760371</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col8\" class=\"data row0 col8\" >0.712029</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col9\" class=\"data row0 col9\" >0.744195</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col10\" class=\"data row0 col10\" >0.699818</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col11\" class=\"data row0 col11\" >0.746858</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row0_col12\" class=\"data row0 col12\" >0.707566</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >Sentiment negative</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col0\" class=\"data row1 col0\" >0.619086</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col1\" class=\"data row1 col1\" >0.521926</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col2\" class=\"data row1 col2\" >0.097159</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col3\" class=\"data row1 col3\" >0.647940</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col4\" class=\"data row1 col4\" >0.510268</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col5\" class=\"data row1 col5\" >0.631305</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col6\" class=\"data row1 col6\" >0.520539</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col7\" class=\"data row1 col7\" >0.625239</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col8\" class=\"data row1 col8\" >0.531997</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col9\" class=\"data row1 col9\" >0.591482</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col10\" class=\"data row1 col10\" >0.518820</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col11\" class=\"data row1 col11\" >0.599462</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row1_col12\" class=\"data row1 col12\" >0.528007</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >Sentiment neutral</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col0\" class=\"data row2 col0\" >0.977339</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col1\" class=\"data row2 col1\" >0.975011</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col2\" class=\"data row2 col2\" >0.002328</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col3\" class=\"data row2 col3\" >0.977580</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col4\" class=\"data row2 col4\" >0.976076</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col5\" class=\"data row2 col5\" >0.977438</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col6\" class=\"data row2 col6\" >0.975311</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col7\" class=\"data row2 col7\" >0.976832</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col8\" class=\"data row2 col8\" >0.975791</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col9\" class=\"data row2 col9\" >0.978005</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col10\" class=\"data row2 col10\" >0.972472</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col11\" class=\"data row2 col11\" >0.976839</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row2_col12\" class=\"data row2 col12\" >0.975404</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >Sentiment positive</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col0\" class=\"data row3 col0\" >0.600698</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col1\" class=\"data row3 col1\" >0.523114</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col2\" class=\"data row3 col2\" >0.077584</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col3\" class=\"data row3 col3\" >0.619773</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col4\" class=\"data row3 col4\" >0.531820</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col5\" class=\"data row3 col5\" >0.618932</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col6\" class=\"data row3 col6\" >0.515704</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col7\" class=\"data row3 col7\" >0.602470</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col8\" class=\"data row3 col8\" >0.533688</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col9\" class=\"data row3 col9\" >0.579758</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col10\" class=\"data row3 col10\" >0.510840</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col11\" class=\"data row3 col11\" >0.582559</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row3_col12\" class=\"data row3 col12\" >0.523518</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >0 <= text tokens < 3</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col0\" class=\"data row4 col0\" >0.958596</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col1\" class=\"data row4 col1\" >0.960171</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col2\" class=\"data row4 col2\" >-0.001575</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.960417</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col4\" class=\"data row4 col4\" >0.951923</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col5\" class=\"data row4 col5\" >0.956332</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col6\" class=\"data row4 col6\" >0.968254</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col7\" class=\"data row4 col7\" >0.955882</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col8\" class=\"data row4 col8\" >0.981481</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col9\" class=\"data row4 col9\" >0.970982</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col10\" class=\"data row4 col10\" >0.926471</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col11\" class=\"data row4 col11\" >0.949367</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row4_col12\" class=\"data row4 col12\" >0.972727</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >3 <= text tokens < 20</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col0\" class=\"data row5 col0\" >0.786084</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col1\" class=\"data row5 col1\" >0.741731</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col2\" class=\"data row5 col2\" >0.044353</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.798427</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col4\" class=\"data row5 col4\" >0.739990</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col5\" class=\"data row5 col5\" >0.792634</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col6\" class=\"data row5 col6\" >0.744394</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col7\" class=\"data row5 col7\" >0.788307</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col8\" class=\"data row5 col8\" >0.750060</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col9\" class=\"data row5 col9\" >0.775244</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col10\" class=\"data row5 col10\" >0.729833</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col11\" class=\"data row5 col11\" >0.775806</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row5_col12\" class=\"data row5 col12\" >0.744376</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >20 <= text tokens < 40</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col0\" class=\"data row6 col0\" >0.717246</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col1\" class=\"data row6 col1\" >0.652513</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col2\" class=\"data row6 col2\" >0.064733</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.733914</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col4\" class=\"data row6 col4\" >0.654745</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col5\" class=\"data row6 col5\" >0.729572</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col6\" class=\"data row6 col6\" >0.646004</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col7\" class=\"data row6 col7\" >0.719126</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col8\" class=\"data row6 col8\" >0.659391</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col9\" class=\"data row6 col9\" >0.698701</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col10\" class=\"data row6 col10\" >0.652018</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col11\" class=\"data row6 col11\" >0.704915</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row6_col12\" class=\"data row6 col12\" >0.650406</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >40 <= text tokens < 64</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col0\" class=\"data row7 col0\" >0.690857</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col1\" class=\"data row7 col1\" >0.616433</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col2\" class=\"data row7 col2\" >0.074424</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0.719694</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col4\" class=\"data row7 col4\" >0.601546</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col5\" class=\"data row7 col5\" >0.717039</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col6\" class=\"data row7 col6\" >0.549581</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col7\" class=\"data row7 col7\" >0.685950</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col8\" class=\"data row7 col8\" >0.580683</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col9\" class=\"data row7 col9\" >0.674592</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col10\" class=\"data row7 col10\" >0.646814</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col11\" class=\"data row7 col11\" >0.657008</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row7_col12\" class=\"data row7 col12\" >0.703540</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >64 <= text tokens < 120</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col0\" class=\"data row8 col0\" >0.675214</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col1\" class=\"data row8 col1\" >0.621795</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col2\" class=\"data row8 col2\" >0.053419</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col3\" class=\"data row8 col3\" >0.666667</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col4\" class=\"data row8 col4\" >0.576923</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col5\" class=\"data row8 col5\" >0.688034</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col6\" class=\"data row8 col6\" >nan</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col7\" class=\"data row8 col7\" >0.666667</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col8\" class=\"data row8 col8\" >nan</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col9\" class=\"data row8 col9\" >0.688034</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col10\" class=\"data row8 col10\" >nan</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col11\" class=\"data row8 col11\" >0.666667</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row8_col12\" class=\"data row8 col12\" >0.666667</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >0 <= selected text tokens < 3</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col0\" class=\"data row9 col0\" >0.690676</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col1\" class=\"data row9 col1\" >0.599791</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col2\" class=\"data row9 col2\" >0.090884</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col3\" class=\"data row9 col3\" >0.714123</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.592912</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col5\" class=\"data row9 col5\" >0.707723</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col6\" class=\"data row9 col6\" >0.607628</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col7\" class=\"data row9 col7\" >0.725638</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col8\" class=\"data row9 col8\" >0.638328</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col9\" class=\"data row9 col9\" >0.661733</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col10\" class=\"data row9 col10\" >0.578395</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col11\" class=\"data row9 col11\" >0.644160</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row9_col12\" class=\"data row9 col12\" >0.581692</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >3 <= selected text tokens < 20</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col0\" class=\"data row10 col0\" >0.748393</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col1\" class=\"data row10 col1\" >0.702346</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col2\" class=\"data row10 col2\" >0.046046</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col3\" class=\"data row10 col3\" >0.761513</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col4\" class=\"data row10 col4\" >0.705028</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col5\" class=\"data row10 col5\" >0.755824</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col6\" class=\"data row10 col6\" >0.692316</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col7\" class=\"data row10 col7\" >0.735372</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col8\" class=\"data row10 col8\" >0.696206</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col9\" class=\"data row10 col9\" >0.737854</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col10\" class=\"data row10 col10\" >0.702492</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col11\" class=\"data row10 col11\" >0.751400</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row10_col12\" class=\"data row10 col12\" >0.715691</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >20 <= selected text tokens < 40</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col0\" class=\"data row11 col0\" >0.897430</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col1\" class=\"data row11 col1\" >0.884514</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col2\" class=\"data row11 col2\" >0.012916</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col3\" class=\"data row11 col3\" >0.900918</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col4\" class=\"data row11 col4\" >0.887036</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col5\" class=\"data row11 col5\" >0.900722</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col6\" class=\"data row11 col6\" >0.880469</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col7\" class=\"data row11 col7\" >0.894571</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col8\" class=\"data row11 col8\" >0.880839</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col9\" class=\"data row11 col9\" >0.894236</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col10\" class=\"data row11 col10\" >0.891220</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col11\" class=\"data row11 col11\" >0.896702</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row11_col12\" class=\"data row11 col12\" >0.883009</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row12\" class=\"row_heading level0 row12\" >40 <= selected text tokens < 64</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col0\" class=\"data row12 col0\" >0.933472</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col1\" class=\"data row12 col1\" >0.936711</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col2\" class=\"data row12 col2\" >-0.003239</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col3\" class=\"data row12 col3\" >0.917098</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col4\" class=\"data row12 col4\" >0.972262</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col5\" class=\"data row12 col5\" >0.950287</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col6\" class=\"data row12 col6\" >0.866835</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col7\" class=\"data row12 col7\" >0.931574</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col8\" class=\"data row12 col8\" >0.930703</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col9\" class=\"data row12 col9\" >0.943858</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col10\" class=\"data row12 col10\" >0.955489</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col11\" class=\"data row12 col11\" >0.924544</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row12_col12\" class=\"data row12 col12\" >0.958266</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002level0_row13\" class=\"row_heading level0 row13\" >64 <= selected text tokens < 120</th>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col0\" class=\"data row13 col0\" >0.698718</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col1\" class=\"data row13 col1\" >0.576923</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col2\" class=\"data row13 col2\" >0.121795</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col3\" class=\"data row13 col3\" >nan</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col4\" class=\"data row13 col4\" >0.576923</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col5\" class=\"data row13 col5\" >0.730769</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col6\" class=\"data row13 col6\" >nan</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col7\" class=\"data row13 col7\" >0.666667</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col8\" class=\"data row13 col8\" >nan</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col9\" class=\"data row13 col9\" >0.730769</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col10\" class=\"data row13 col10\" >nan</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col11\" class=\"data row13 col11\" >0.666667</td>\n","                        <td id=\"T_d15ba528_9f4c_11ea_a534_0242ac1c0002row13_col12\" class=\"data row13 col12\" >nan</td>\n","            </tr>\n","    </tbody></table>"],"text/plain":["<pandas.io.formats.style.Styler at 0x7f4f48b24128>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"yP3xG-Cenvry","colab_type":"text"},"source":["# Visualize predictions"]},{"cell_type":"code","metadata":{"_kg_hide-input":true,"id":"cGxcMVRMnvrz","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":581},"cellView":"form","outputId":"328b554c-998d-4663-d978-ff2718a95619","executionInfo":{"status":"ok","timestamp":1590494433288,"user_tz":180,"elapsed":1006145,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","display(k_fold[[c for c in k_fold.columns if not (c.startswith('textID') or \n","                                                  c.startswith('text_len') or \n","                                                  c.startswith('selected_text_len') or \n","                                                  c.startswith('text_wordCnt') or \n","                                                  c.startswith('selected_text_wordCnt') or \n","                                                  c.startswith('fold_') or \n","                                                  c.startswith('start_fold_') or \n","                                                  c.startswith('end_fold_'))]].head(15))"],"execution_count":15,"outputs":[{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>sentiment</th>\n","      <th>jaccard</th>\n","      <th>text_tokenCnt</th>\n","      <th>selected_text_tokenCnt</th>\n","      <th>imputed</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>i`d have responded, if i were going</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>10</td>\n","      <td>10</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>sooo sad i will miss you here in san diego!!!</td>\n","      <td>sooo sad</td>\n","      <td>negative</td>\n","      <td>0.200000</td>\n","      <td>13</td>\n","      <td>3</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>my boss is bullying me...</td>\n","      <td>bullying me</td>\n","      <td>negative</td>\n","      <td>0.166667</td>\n","      <td>6</td>\n","      <td>2</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>what interview! leave me alone</td>\n","      <td>leave me alone</td>\n","      <td>negative</td>\n","      <td>0.600000</td>\n","      <td>6</td>\n","      <td>3</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>sons of ****, why couldn`t they put them on the releases we already bought</td>\n","      <td>sons of ****,</td>\n","      <td>negative</td>\n","      <td>0.214286</td>\n","      <td>17</td>\n","      <td>4</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>http://www.dothebouncy.com/smf - some shameless plugging for the best rangers forum on earth</td>\n","      <td>http://www.dothebouncy.com/smf - some shameless plugging for the best rangers forum on earth</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>27</td>\n","      <td>27</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>2am feedings for the baby are fun when he is all smiles and coos</td>\n","      <td>fun</td>\n","      <td>positive</td>\n","      <td>0.071429</td>\n","      <td>17</td>\n","      <td>1</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>soooo high</td>\n","      <td>soooo high</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>both of you</td>\n","      <td>both of you</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>journey!? wow... u just became cooler.  hehe... (is that possible!?)</td>\n","      <td>wow... u just became cooler.</td>\n","      <td>positive</td>\n","      <td>0.500000</td>\n","      <td>19</td>\n","      <td>7</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>as much as i love to be hopeful, i reckon the chances are minimal =p i`m never gonna get my cake and stuff</td>\n","      <td>as much as i love to be hopeful, i reckon the chances are minimal =p i`m never gonna get my cake and stuff</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>27</td>\n","      <td>27</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>i really really like the song love story by taylor swift</td>\n","      <td>like</td>\n","      <td>positive</td>\n","      <td>0.100000</td>\n","      <td>12</td>\n","      <td>1</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>my sharpie is running dangerously low on ink</td>\n","      <td>dangerously</td>\n","      <td>negative</td>\n","      <td>0.125000</td>\n","      <td>9</td>\n","      <td>1</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>i want to go to music tonight but i lost my voice.</td>\n","      <td>lost</td>\n","      <td>negative</td>\n","      <td>0.100000</td>\n","      <td>13</td>\n","      <td>1</td>\n","      <td>False</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>test test from the lg env2</td>\n","      <td>test test from the lg env2</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>8</td>\n","      <td>8</td>\n","      <td>False</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                                                                                                          text  ... imputed\n","0                                                                          i`d have responded, if i were going  ...   False\n","1                                                                sooo sad i will miss you here in san diego!!!  ...   False\n","2                                                                                    my boss is bullying me...  ...   False\n","3                                                                               what interview! leave me alone  ...   False\n","4                                   sons of ****, why couldn`t they put them on the releases we already bought  ...   False\n","5                 http://www.dothebouncy.com/smf - some shameless plugging for the best rangers forum on earth  ...   False\n","6                                             2am feedings for the baby are fun when he is all smiles and coos  ...   False\n","7                                                                                                   soooo high  ...   False\n","8                                                                                                  both of you  ...   False\n","9                                         journey!? wow... u just became cooler.  hehe... (is that possible!?)  ...   False\n","10  as much as i love to be hopeful, i reckon the chances are minimal =p i`m never gonna get my cake and stuff  ...   False\n","11                                                    i really really like the song love story by taylor swift  ...   False\n","12                                                                my sharpie is running dangerously low on ink  ...   False\n","13                                                          i want to go to music tonight but i lost my voice.  ...   False\n","14                                                                                  test test from the lg env2  ...   False\n","\n","[15 rows x 7 columns]"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"wswPoUt1zZLs","colab_type":"text"},"source":["## Post-processing evaluation"]},{"cell_type":"code","metadata":{"id":"j_sRri2DIY2o","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":376},"cellView":"form","outputId":"bc2415d5-ccea-4cc7-8273-fb0c650dc442","executionInfo":{"status":"ok","timestamp":1590495916882,"user_tz":180,"elapsed":17860,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","k_fold_best_post = k_fold_best.copy()\n","k_fold_best_post.loc[k_fold_best_post['sentiment'] == 'neutral', 'selected_text'] = k_fold_best_post[\"text\"]\n","print('\\nImpute neutral')\n","display(evaluate_model_kfold(k_fold_best_post, config['N_FOLDS']).head(1).style.applymap(color_map))\n","\n","k_fold_best_post = k_fold_best.copy()\n","k_fold_best_post.loc[k_fold_best_post['text_wordCnt'] <= 3, 'selected_text'] = k_fold_best_post[\"text\"]\n","print('\\nImpute <= 3')\n","display(evaluate_model_kfold(k_fold_best_post, config['N_FOLDS']).head(1).style.applymap(color_map))\n","\n","k_fold_best_post = k_fold_best.copy()\n","k_fold_best_post.loc[k_fold_best_post['sentiment'] == 'neutral', 'selected_text'] = k_fold_best_post[\"text\"]\n","k_fold_best_post.loc[k_fold_best_post['text_wordCnt'] <= 3, 'selected_text'] = k_fold_best_post[\"text\"]\n","print('\\nImpute neutral nao <= 3')\n","display(evaluate_model_kfold(k_fold_best_post, config['N_FOLDS']).head(1).style.applymap(color_map))\n","\n","k_fold_best_post = k_fold_best.copy()\n","k_fold_best_post['selected_text'] = k_fold_best_post['selected_text'].apply(lambda x: x.replace('!!!!', '!') if len(x.split())==1 else x)\n","k_fold_best_post['selected_text'] = k_fold_best_post['selected_text'].apply(lambda x: x.replace('..', '.') if len(x.split())==1 else x)\n","k_fold_best_post['selected_text'] = k_fold_best_post['selected_text'].apply(lambda x: x.replace('...', '.') if len(x.split())==1 else x)\n","print('\\nImpute noise')\n","display(evaluate_model_kfold(k_fold_best_post, config['N_FOLDS']).head(1).style.applymap(color_map))"],"execution_count":34,"outputs":[{"output_type":"stream","text":["\n","Impute neutral\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["<style  type=\"text/css\" >\n","    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col0 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col1 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col2 {\n","            color:  red;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col3 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col4 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col5 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col6 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col7 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col8 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col9 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col10 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col11 {\n","            color:  black;\n","        }    #T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col12 {\n","            color:  black;\n","        }</style><table id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Train</th>        <th class=\"col_heading level0 col1\" >Valid</th>        <th class=\"col_heading level0 col2\" >Var</th>        <th class=\"col_heading level0 col3\" >Train_fold_1</th>        <th class=\"col_heading level0 col4\" >Valid_fold_1</th>        <th class=\"col_heading level0 col5\" >Train_fold_2</th>        <th class=\"col_heading level0 col6\" >Valid_fold_2</th>        <th class=\"col_heading level0 col7\" >Train_fold_3</th>        <th class=\"col_heading level0 col8\" >Valid_fold_3</th>        <th class=\"col_heading level0 col9\" >Train_fold_4</th>        <th class=\"col_heading level0 col10\" >Valid_fold_4</th>        <th class=\"col_heading level0 col11\" >Train_fold_5</th>        <th class=\"col_heading level0 col12\" >Valid_fold_5</th>    </tr>    <tr>        <th class=\"index_name level0\" >Metric/Jaccard</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n","                <tr>\n","                        <th id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Overall</th>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col0\" class=\"data row0 col0\" >0.763157</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col1\" class=\"data row0 col1\" >0.712074</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col2\" class=\"data row0 col2\" >0.051083</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.777206</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0.711471</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col5\" class=\"data row0 col5\" >0.771427</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col6\" class=\"data row0 col6\" >0.707793</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.764166</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col8\" class=\"data row0 col8\" >0.717391</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col9\" class=\"data row0 col9\" >0.750690</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col10\" class=\"data row0 col10\" >0.709428</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col11\" class=\"data row0 col11\" >0.752296</td>\n","                        <td id=\"T_ed1bc852_9f4b_11ea_a534_0242ac1c0002row0_col12\" class=\"data row0 col12\" >0.714287</td>\n","            </tr>\n","    </tbody></table>"],"text/plain":["<pandas.io.formats.style.Styler at 0x7f4f47512438>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n","Impute <= 3\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["<style  type=\"text/css\" >\n","    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col0 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col1 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col2 {\n","            color:  red;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col3 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col4 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col5 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col6 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col7 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col8 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col9 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col10 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col11 {\n","            color:  black;\n","        }    #T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col12 {\n","            color:  black;\n","        }</style><table id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Train</th>        <th class=\"col_heading level0 col1\" >Valid</th>        <th class=\"col_heading level0 col2\" >Var</th>        <th class=\"col_heading level0 col3\" >Train_fold_1</th>        <th class=\"col_heading level0 col4\" >Valid_fold_1</th>        <th class=\"col_heading level0 col5\" >Train_fold_2</th>        <th class=\"col_heading level0 col6\" >Valid_fold_2</th>        <th class=\"col_heading level0 col7\" >Train_fold_3</th>        <th class=\"col_heading level0 col8\" >Valid_fold_3</th>        <th class=\"col_heading level0 col9\" >Train_fold_4</th>        <th class=\"col_heading level0 col10\" >Valid_fold_4</th>        <th class=\"col_heading level0 col11\" >Train_fold_5</th>        <th class=\"col_heading level0 col12\" >Valid_fold_5</th>    </tr>    <tr>        <th class=\"index_name level0\" >Metric/Jaccard</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n","                <tr>\n","                        <th id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Overall</th>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col0\" class=\"data row0 col0\" >0.756724</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col1\" class=\"data row0 col1\" >0.705064</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col2\" class=\"data row0 col2\" >0.051660</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.770705</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0.705195</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col5\" class=\"data row0 col5\" >0.765488</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col6\" class=\"data row0 col6\" >0.701010</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.758056</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col8\" class=\"data row0 col8\" >0.710099</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col9\" class=\"data row0 col9\" >0.743431</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col10\" class=\"data row0 col10\" >0.701370</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col11\" class=\"data row0 col11\" >0.745941</td>\n","                        <td id=\"T_ef960f16_9f4b_11ea_a534_0242ac1c0002row0_col12\" class=\"data row0 col12\" >0.707645</td>\n","            </tr>\n","    </tbody></table>"],"text/plain":["<pandas.io.formats.style.Styler at 0x7f50c2c78320>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n","Impute neutral nao <= 3\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["<style  type=\"text/css\" >\n","    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col0 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col1 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col2 {\n","            color:  red;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col3 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col4 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col5 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col6 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col7 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col8 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col9 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col10 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col11 {\n","            color:  black;\n","        }    #T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col12 {\n","            color:  black;\n","        }</style><table id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Train</th>        <th class=\"col_heading level0 col1\" >Valid</th>        <th class=\"col_heading level0 col2\" >Var</th>        <th class=\"col_heading level0 col3\" >Train_fold_1</th>        <th class=\"col_heading level0 col4\" >Valid_fold_1</th>        <th class=\"col_heading level0 col5\" >Train_fold_2</th>        <th class=\"col_heading level0 col6\" >Valid_fold_2</th>        <th class=\"col_heading level0 col7\" >Train_fold_3</th>        <th class=\"col_heading level0 col8\" >Valid_fold_3</th>        <th class=\"col_heading level0 col9\" >Train_fold_4</th>        <th class=\"col_heading level0 col10\" >Valid_fold_4</th>        <th class=\"col_heading level0 col11\" >Train_fold_5</th>        <th class=\"col_heading level0 col12\" >Valid_fold_5</th>    </tr>    <tr>        <th class=\"index_name level0\" >Metric/Jaccard</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n","                <tr>\n","                        <th id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Overall</th>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col0\" class=\"data row0 col0\" >0.762215</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col1\" class=\"data row0 col1\" >0.711900</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col2\" class=\"data row0 col2\" >0.050315</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.775939</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0.711865</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col5\" class=\"data row0 col5\" >0.770190</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col6\" class=\"data row0 col6\" >0.706883</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.762436</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col8\" class=\"data row0 col8\" >0.715874</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col9\" class=\"data row0 col9\" >0.750522</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col10\" class=\"data row0 col10\" >0.710474</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col11\" class=\"data row0 col11\" >0.751989</td>\n","                        <td id=\"T_f20fac16_9f4b_11ea_a534_0242ac1c0002row0_col12\" class=\"data row0 col12\" >0.714403</td>\n","            </tr>\n","    </tbody></table>"],"text/plain":["<pandas.io.formats.style.Styler at 0x7f50c2c789e8>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n","Impute noise\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["<style  type=\"text/css\" >\n","    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col0 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col1 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col2 {\n","            color:  red;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col3 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col4 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col5 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col6 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col7 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col8 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col9 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col10 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col11 {\n","            color:  black;\n","        }    #T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col12 {\n","            color:  black;\n","        }</style><table id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Train</th>        <th class=\"col_heading level0 col1\" >Valid</th>        <th class=\"col_heading level0 col2\" >Var</th>        <th class=\"col_heading level0 col3\" >Train_fold_1</th>        <th class=\"col_heading level0 col4\" >Valid_fold_1</th>        <th class=\"col_heading level0 col5\" >Train_fold_2</th>        <th class=\"col_heading level0 col6\" >Valid_fold_2</th>        <th class=\"col_heading level0 col7\" >Train_fold_3</th>        <th class=\"col_heading level0 col8\" >Valid_fold_3</th>        <th class=\"col_heading level0 col9\" >Train_fold_4</th>        <th class=\"col_heading level0 col10\" >Valid_fold_4</th>        <th class=\"col_heading level0 col11\" >Train_fold_5</th>        <th class=\"col_heading level0 col12\" >Valid_fold_5</th>    </tr>    <tr>        <th class=\"index_name level0\" >Metric/Jaccard</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n","                <tr>\n","                        <th id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Overall</th>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col0\" class=\"data row0 col0\" >0.755574</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col1\" class=\"data row0 col1\" >0.703165</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col2\" class=\"data row0 col2\" >0.052409</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.769812</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0.702647</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col5\" class=\"data row0 col5\" >0.764747</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col6\" class=\"data row0 col6\" >0.699039</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.757530</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col8\" class=\"data row0 col8\" >0.710281</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col9\" class=\"data row0 col9\" >0.741466</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col10\" class=\"data row0 col10\" >0.698542</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col11\" class=\"data row0 col11\" >0.744316</td>\n","                        <td id=\"T_f49e5428_9f4b_11ea_a534_0242ac1c0002row0_col12\" class=\"data row0 col12\" >0.705317</td>\n","            </tr>\n","    </tbody></table>"],"text/plain":["<pandas.io.formats.style.Styler at 0x7f4f48b24198>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"YBlUsCFUQVYF","colab_type":"text"},"source":["# Error analysis\n","\n","## 10 worst predictions"]},{"cell_type":"code","metadata":{"id":"EvVPpEJA9x8P","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":797},"cellView":"form","outputId":"cac349ff-9b4b-4f3a-9022-3488d4dbdc29","executionInfo":{"status":"ok","timestamp":1590494449612,"user_tz":180,"elapsed":1022458,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","k_fold_best['jaccard_mean'] = (k_fold_best['jaccard_fold_1'] + k_fold_best['jaccard_fold_2'] + \n","                               k_fold_best['jaccard_fold_3'] + k_fold_best['jaccard_fold_4'] + \n","                               k_fold_best['jaccard_fold_4']) / 5\n","\n","display(k_fold_best[['text', 'selected_text', 'sentiment', 'jaccard', 'jaccard_mean', \n","                     'prediction_fold_1', 'prediction_fold_2', 'prediction_fold_3', \n","                     'prediction_fold_4', 'prediction_fold_5']].sort_values(by=['jaccard_mean']).head(10))"],"execution_count":17,"outputs":[{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>sentiment</th>\n","      <th>jaccard</th>\n","      <th>jaccard_mean</th>\n","      <th>prediction_fold_1</th>\n","      <th>prediction_fold_2</th>\n","      <th>prediction_fold_3</th>\n","      <th>prediction_fold_4</th>\n","      <th>prediction_fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>15157</th>\n","      <td>that`s family for you  imna crash, woke up 630 3 days in a row....lol</td>\n","      <td>a crash</td>\n","      <td>negative</td>\n","      <td>0.066667</td>\n","      <td>0.0</td>\n","      <td>imna crash,</td>\n","      <td>crash,</td>\n","      <td>imna crash,</td>\n","      <td>crash,</td>\n","      <td>crash,</td>\n","    </tr>\n","    <tr>\n","      <th>10227</th>\n","      <td>yess... it`s awesomee.. and u can follow ur love molly hahah....  now u can chat with us here!</td>\n","      <td>s awesomee</td>\n","      <td>positive</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>awesomee..</td>\n","      <td>awesomee..</td>\n","      <td>awesomee..</td>\n","      <td>awesomee..</td>\n","      <td>it`s awesomee..</td>\n","    </tr>\n","    <tr>\n","      <th>15502</th>\n","      <td>@_hayles are u serious???? you touched his ****? ohmygod u ****!!! lol aaaaawwwwwww y did u tell me that!!!</td>\n","      <td>****!!</td>\n","      <td>negative</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>ohmygod u ****!!!</td>\n","      <td>ohmygod u ****!!!</td>\n","      <td>ohmygod u ****!!!</td>\n","      <td>aaaaawwwwwww</td>\n","      <td>ohmygod u ****!!!</td>\n","    </tr>\n","    <tr>\n","      <th>17246</th>\n","      <td>rofl</td>\n","      <td>rofl</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>0.0</td>\n","      <td>ro</td>\n","      <td>ro</td>\n","      <td>ro</td>\n","      <td>ro</td>\n","      <td>ro</td>\n","    </tr>\n","    <tr>\n","      <th>4638</th>\n","      <td>it was great to meet ya katie...awesome shows for sure!! safe travels home.</td>\n","      <td>.awesome</td>\n","      <td>positive</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>it was great to meet ya katie...awesome shows for sure!!</td>\n","      <td>wesome shows for sure!!</td>\n","      <td>great</td>\n","      <td>great</td>\n","      <td>it was great</td>\n","    </tr>\n","    <tr>\n","      <th>17247</th>\n","      <td>yeah, tried it. no go.</td>\n","      <td>tried</td>\n","      <td>negative</td>\n","      <td>0.200000</td>\n","      <td>0.0</td>\n","      <td>no go.</td>\n","      <td>no go.</td>\n","      <td>no go.</td>\n","      <td>no go.</td>\n","      <td>no go.</td>\n","    </tr>\n","    <tr>\n","      <th>26313</th>\n","      <td>had plans with people but they cancelled...now what to do?</td>\n","      <td>cancelled..</td>\n","      <td>negative</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>cancelled...</td>\n","      <td>cancelled...</td>\n","      <td>cancelled...</td>\n","      <td>cancelled...</td>\n","      <td>cancelled...</td>\n","    </tr>\n","    <tr>\n","      <th>26307</th>\n","      <td>ahh im in love.  hes theeee best.</td>\n","      <td>best.</td>\n","      <td>positive</td>\n","      <td>0.142857</td>\n","      <td>0.0</td>\n","      <td>ahh im in love.</td>\n","      <td>ahh im in love.</td>\n","      <td>ahh im in love.</td>\n","      <td>ahh im in love.</td>\n","      <td>ahh im in love.</td>\n","    </tr>\n","    <tr>\n","      <th>17257</th>\n","      <td>n case you missed the show yesterday - here`s a chance to listen again on the bbc iplayer  enjoy  http://tiny.cc/oikbk</td>\n","      <td>here`s a chance to listen again on</td>\n","      <td>positive</td>\n","      <td>0.368421</td>\n","      <td>0.0</td>\n","      <td>enjoy</td>\n","      <td>enjoy</td>\n","      <td>enjoy</td>\n","      <td>enjoy</td>\n","      <td>enjoy</td>\n","    </tr>\n","    <tr>\n","      <th>10675</th>\n","      <td>yes</td>\n","      <td>yes</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>0.0</td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                                                                                                                         text  ...  prediction_fold_5\n","15157                                                   that`s family for you  imna crash, woke up 630 3 days in a row....lol  ...             crash,\n","10227                          yess... it`s awesomee.. and u can follow ur love molly hahah....  now u can chat with us here!  ...    it`s awesomee..\n","15502             @_hayles are u serious???? you touched his ****? ohmygod u ****!!! lol aaaaawwwwwww y did u tell me that!!!  ...  ohmygod u ****!!!\n","17246                                                                                                                    rofl  ...                 ro\n","4638                                              it was great to meet ya katie...awesome shows for sure!! safe travels home.  ...       it was great\n","17247                                                                                                  yeah, tried it. no go.  ...             no go.\n","26313                                                              had plans with people but they cancelled...now what to do?  ...       cancelled...\n","26307                                                                                       ahh im in love.  hes theeee best.  ...    ahh im in love.\n","17257  n case you missed the show yesterday - here`s a chance to listen again on the bbc iplayer  enjoy  http://tiny.cc/oikbk  ...              enjoy\n","10675                                                                                                                     yes  ...                   \n","\n","[10 rows x 10 columns]"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"oWpJisngSFX2","colab_type":"text"},"source":["# Sentiment"]},{"cell_type":"code","metadata":{"id":"9oazyItBSH8x","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":1000},"cellView":"form","outputId":"a93afab8-6d70-46ab-b235-858a26f64dfc","executionInfo":{"status":"ok","timestamp":1590494449613,"user_tz":180,"elapsed":1022454,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","print('\\n sentiment == neutral')\n","display(k_fold_best[k_fold_best['sentiment'] == 'neutral'][['text', 'selected_text', \n","                                                            'jaccard_mean', 'prediction_fold_1', \n","                                                            'prediction_fold_2', 'prediction_fold_3', \n","                                                            'prediction_fold_4', 'prediction_fold_5']].sort_values(by=['jaccard_mean']).head(10))\n","\n","print('\\n sentiment == positive')\n","display(k_fold_best[k_fold_best['sentiment'] == 'positive'][['text', 'selected_text', \n","                                                            'jaccard_mean', 'prediction_fold_1', \n","                                                            'prediction_fold_2', 'prediction_fold_3', \n","                                                            'prediction_fold_4', 'prediction_fold_5']].sort_values(by=['jaccard_mean']).head(10))\n","\n","print('\\n sentiment == negative')\n","display(k_fold_best[k_fold_best['sentiment'] == 'negative'][['text', 'selected_text', \n","                                                            'jaccard_mean', 'prediction_fold_1', \n","                                                            'prediction_fold_2', 'prediction_fold_3', \n","                                                            'prediction_fold_4', 'prediction_fold_5']].sort_values(by=['jaccard_mean']).head(10))"],"execution_count":18,"outputs":[{"output_type":"stream","text":["\n"," sentiment == neutral\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>jaccard_mean</th>\n","      <th>prediction_fold_1</th>\n","      <th>prediction_fold_2</th>\n","      <th>prediction_fold_3</th>\n","      <th>prediction_fold_4</th>\n","      <th>prediction_fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>11455</th>\n","      <td>yup</td>\n","      <td>yup</td>\n","      <td>0.0</td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","    </tr>\n","    <tr>\n","      <th>25690</th>\n","      <td>@_cheshire_cat_</td>\n","      <td>_cheshire_cat_</td>\n","      <td>0.0</td>\n","      <td>@_cheshire_cat_</td>\n","      <td>@_cheshire_cat_</td>\n","      <td>@_cheshire_cat_</td>\n","      <td>@_cheshire_cat_</td>\n","      <td>@_cheshire_cat_</td>\n","    </tr>\n","    <tr>\n","      <th>16473</th>\n","      <td>not</td>\n","      <td>not</td>\n","      <td>0.0</td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","    </tr>\n","    <tr>\n","      <th>3262</th>\n","      <td>_inthemaking :aw</td>\n","      <td>aw</td>\n","      <td>0.0</td>\n","      <td>_inthemaking :aw</td>\n","      <td>_inthemaking :aw</td>\n","      <td>_inthemaking :aw</td>\n","      <td>_inthemaking :aw</td>\n","      <td>_inthemaking :aw</td>\n","    </tr>\n","    <tr>\n","      <th>3446</th>\n","      <td>why?</td>\n","      <td>why?</td>\n","      <td>0.0</td>\n","      <td>why</td>\n","      <td>why</td>\n","      <td>why</td>\n","      <td>why</td>\n","      <td>why</td>\n","    </tr>\n","    <tr>\n","      <th>12361</th>\n","      <td>ikr!!!</td>\n","      <td>ikr!!!</td>\n","      <td>0.0</td>\n","      <td>kr</td>\n","      <td>kr</td>\n","      <td>kr</td>\n","      <td>kr</td>\n","      <td>kr</td>\n","    </tr>\n","    <tr>\n","      <th>24209</th>\n","      <td>byeeeee!!!</td>\n","      <td>byeeeee!!</td>\n","      <td>0.0</td>\n","      <td>byeeeee!!!</td>\n","      <td>byeeeee!!!</td>\n","      <td>byeeeee!!!</td>\n","      <td>byeeeee!!!</td>\n","      <td>byeeeee!!!</td>\n","    </tr>\n","    <tr>\n","      <th>24068</th>\n","      <td>g`night!</td>\n","      <td>g`night</td>\n","      <td>0.0</td>\n","      <td>g`night!</td>\n","      <td>g`night!</td>\n","      <td>g`night!</td>\n","      <td>g`night!</td>\n","      <td>g`night!</td>\n","    </tr>\n","    <tr>\n","      <th>17246</th>\n","      <td>rofl</td>\n","      <td>rofl</td>\n","      <td>0.0</td>\n","      <td>ro</td>\n","      <td>ro</td>\n","      <td>ro</td>\n","      <td>ro</td>\n","      <td>ro</td>\n","    </tr>\n","    <tr>\n","      <th>23659</th>\n","      <td>why?</td>\n","      <td>why?</td>\n","      <td>0.0</td>\n","      <td>why</td>\n","      <td>why</td>\n","      <td>why</td>\n","      <td>why</td>\n","      <td>why</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                   text   selected_text  ...  prediction_fold_4 prediction_fold_5\n","11455               yup             yup  ...                                     \n","25690   @_cheshire_cat_  _cheshire_cat_  ...    @_cheshire_cat_   @_cheshire_cat_\n","16473               not             not  ...                                     \n","3262   _inthemaking :aw              aw  ...   _inthemaking :aw  _inthemaking :aw\n","3446               why?            why?  ...                why               why\n","12361            ikr!!!          ikr!!!  ...                 kr                kr\n","24209        byeeeee!!!       byeeeee!!  ...         byeeeee!!!        byeeeee!!!\n","24068          g`night!         g`night  ...           g`night!          g`night!\n","17246              rofl            rofl  ...                 ro                ro\n","23659              why?            why?  ...                why               why\n","\n","[10 rows x 8 columns]"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"," sentiment == positive\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>jaccard_mean</th>\n","      <th>prediction_fold_1</th>\n","      <th>prediction_fold_2</th>\n","      <th>prediction_fold_3</th>\n","      <th>prediction_fold_4</th>\n","      <th>prediction_fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>24504</th>\n","      <td>http://twitpic.com/4hsd2 - weheyyyy   we give thanks for midi keyboards</td>\n","      <td>ve thank</td>\n","      <td>0.0</td>\n","      <td>give thanks</td>\n","      <td>we give thanks</td>\n","      <td>we give thanks</td>\n","      <td>we give thanks</td>\n","      <td>we give thanks</td>\n","    </tr>\n","    <tr>\n","      <th>20565</th>\n","      <td>now i know my shares are up...have 7 followers...wonderful!   the sun is now shining brightly in `darkest africa`...</td>\n","      <td>wonderful!   the sun is now shining brightly in `darkest africa</td>\n","      <td>0.0</td>\n","      <td>onderful!</td>\n","      <td>onderful!</td>\n","      <td>onderful!</td>\n","      <td>onderful!</td>\n","      <td>onderful!</td>\n","    </tr>\n","    <tr>\n","      <th>6685</th>\n","      <td>good morning miamiadc  my weekend was great and i just had my monday, which was also great  i hope you have a wonder...</td>\n","      <td>a wonderfu</td>\n","      <td>0.0</td>\n","      <td>good morning miamiadc  my weekend was great</td>\n","      <td>my weekend was great</td>\n","      <td>my weekend was great</td>\n","      <td>good morning miamiadc  my weekend was great</td>\n","      <td>good morning miamiadc  my weekend was great</td>\n","    </tr>\n","    <tr>\n","      <th>23637</th>\n","      <td>thanks for that, now i learned something new today  enjoy.</td>\n","      <td>enjoy</td>\n","      <td>0.0</td>\n","      <td>thanks for that,</td>\n","      <td>thanks for that, now i learned something new today  enjoy.</td>\n","      <td>thanks for that, now i learned something new today  enjoy.</td>\n","      <td>thanks for that, now i learned something new today  enjoy.</td>\n","      <td>thanks for that, now i learned something new today  enjoy.</td>\n","    </tr>\n","    <tr>\n","      <th>13802</th>\n","      <td>forgot she had a twitter account.    happy mother`s day!</td>\n","      <td>happ</td>\n","      <td>0.0</td>\n","      <td>happy</td>\n","      <td>happy</td>\n","      <td>happy</td>\n","      <td>happy</td>\n","      <td>happy</td>\n","    </tr>\n","    <tr>\n","      <th>10998</th>\n","      <td>is maxin and relaxin... ahhh</td>\n","      <td>relaxin..</td>\n","      <td>0.0</td>\n","      <td>relaxin... ahhh</td>\n","      <td>ahhh</td>\n","      <td>relaxin...</td>\n","      <td>relaxin...</td>\n","      <td>relaxin...</td>\n","    </tr>\n","    <tr>\n","      <th>23616</th>\n","      <td>just saw it tonight as well... great movie!!  hope you`re well mate! cheers e</td>\n","      <td>.. grea</td>\n","      <td>0.0</td>\n","      <td>great movie!!</td>\n","      <td>great movie!!</td>\n","      <td>great movie!!</td>\n","      <td>great movie!!</td>\n","      <td>great movie!!</td>\n","    </tr>\n","    <tr>\n","      <th>20655</th>\n","      <td>he he ...happy #star wars day! may the 4th be with you  brilliant!!</td>\n","      <td>happy #star wars day!</td>\n","      <td>0.0</td>\n","      <td>appy</td>\n","      <td>appy</td>\n","      <td>appy</td>\n","      <td>appy</td>\n","      <td>appy</td>\n","    </tr>\n","    <tr>\n","      <th>5188</th>\n","      <td>http://twitpic.com/4wc1y - cracking myself more &amp; more up..  phootoboothingisfunforbunny volumen eins!</td>\n","      <td>sfunf</td>\n","      <td>0.0</td>\n","      <td>cracking</td>\n","      <td>phootoboothingisfunforbunny volumen eins!</td>\n","      <td>cracking myself more &amp; more up..  phootoboothingisfunforbunny volumen eins!</td>\n","      <td>cracking myself more &amp; more up..  phootoboothingisfunforbunny volumen eins!</td>\n","      <td>cracking myself more &amp; more up..</td>\n","    </tr>\n","    <tr>\n","      <th>8002</th>\n","      <td>_d awww glad to know little sweet d and leigh are doing good...thanks for the updates howie</td>\n","      <td>little sweet d and leigh are doing good...thanks for the updates ho</td>\n","      <td>0.0</td>\n","      <td>glad</td>\n","      <td>glad</td>\n","      <td>glad</td>\n","      <td>glad</td>\n","      <td>glad</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                                                                                                                          text  ...                                           prediction_fold_5\n","24504                                                  http://twitpic.com/4hsd2 - weheyyyy   we give thanks for midi keyboards  ...                                              we give thanks\n","20565     now i know my shares are up...have 7 followers...wonderful!   the sun is now shining brightly in `darkest africa`...  ...                                                   onderful!\n","6685   good morning miamiadc  my weekend was great and i just had my monday, which was also great  i hope you have a wonder...  ...                 good morning miamiadc  my weekend was great\n","23637                                                               thanks for that, now i learned something new today  enjoy.  ...  thanks for that, now i learned something new today  enjoy.\n","13802                                                                 forgot she had a twitter account.    happy mother`s day!  ...                                                       happy\n","10998                                                                                             is maxin and relaxin... ahhh  ...                                                  relaxin...\n","23616                                            just saw it tonight as well... great movie!!  hope you`re well mate! cheers e  ...                                               great movie!!\n","20655                                                      he he ...happy #star wars day! may the 4th be with you  brilliant!!  ...                                                        appy\n","5188                    http://twitpic.com/4wc1y - cracking myself more & more up..  phootoboothingisfunforbunny volumen eins!  ...                            cracking myself more & more up..\n","8002                               _d awww glad to know little sweet d and leigh are doing good...thanks for the updates howie  ...                                                        glad\n","\n","[10 rows x 8 columns]"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"," sentiment == negative\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>jaccard_mean</th>\n","      <th>prediction_fold_1</th>\n","      <th>prediction_fold_2</th>\n","      <th>prediction_fold_3</th>\n","      <th>prediction_fold_4</th>\n","      <th>prediction_fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>9725</th>\n","      <td>my tummy hurts...again</td>\n","      <td>hurts..</td>\n","      <td>0.0</td>\n","      <td>hurts...</td>\n","      <td>hurts...</td>\n","      <td>hurts...</td>\n","      <td>hurts...again</td>\n","      <td>hurts...again</td>\n","    </tr>\n","    <tr>\n","      <th>22985</th>\n","      <td>y am i still awake!!!! smh.... this sucks!!!</td>\n","      <td>sucks!!</td>\n","      <td>0.0</td>\n","      <td>sucks!!!</td>\n","      <td>sucks!!!</td>\n","      <td>sucks!!!</td>\n","      <td>sucks!!!</td>\n","      <td>sucks!!!</td>\n","    </tr>\n","    <tr>\n","      <th>19780</th>\n","      <td>i think my modem failed-having pc withdrawals..</td>\n","      <td>i think my modem failed-having pc withdrawals..</td>\n","      <td>0.0</td>\n","      <td>failed-</td>\n","      <td>failed-</td>\n","      <td>failed-</td>\n","      <td>failed-</td>\n","      <td>failed-</td>\n","    </tr>\n","    <tr>\n","      <th>3671</th>\n","      <td>is not feelin well... i feel sooooo weak....i hate bein sick in the summer</td>\n","      <td>weak..</td>\n","      <td>0.0</td>\n","      <td>i feel sooooo weak....i hate bein sick in the summer</td>\n","      <td>hate bein sick in the summer</td>\n","      <td>weak....</td>\n","      <td>hate bein sick in the summer</td>\n","      <td>is not feelin well... i feel sooooo weak....</td>\n","    </tr>\n","    <tr>\n","      <th>1149</th>\n","      <td>but they are expensive.</td>\n","      <td>e expensive</td>\n","      <td>0.0</td>\n","      <td>expensive.</td>\n","      <td>expensive.</td>\n","      <td>expensive.</td>\n","      <td>expensive.</td>\n","      <td>expensive.</td>\n","    </tr>\n","    <tr>\n","      <th>15735</th>\n","      <td>i know what you mean  rain sucks...</td>\n","      <td>n sucks</td>\n","      <td>0.0</td>\n","      <td>rain sucks...</td>\n","      <td>rain sucks...</td>\n","      <td>rain sucks...</td>\n","      <td>rain sucks...</td>\n","      <td>rain sucks...</td>\n","    </tr>\n","    <tr>\n","      <th>3677</th>\n","      <td>migranes suck....especially when the kids are suddenly hyper.</td>\n","      <td>suck..</td>\n","      <td>0.0</td>\n","      <td>suck....</td>\n","      <td>suck....</td>\n","      <td>suck....</td>\n","      <td>suck....</td>\n","      <td>suck....</td>\n","    </tr>\n","    <tr>\n","      <th>9838</th>\n","      <td>is so frustrated!!! i`m stuck at home without any transportation to the global god conference!!! ahh</td>\n","      <td>so frustrated!!</td>\n","      <td>0.0</td>\n","      <td>frustrated!!!</td>\n","      <td>frustrated!!!</td>\n","      <td>frustrated!!!</td>\n","      <td>frustrated!!!</td>\n","      <td>frustrated!!!</td>\n","    </tr>\n","    <tr>\n","      <th>22948</th>\n","      <td>srsly, bgt, joke maaan. how lame. ughhhh work tomorah have to get up early</td>\n","      <td>ughhhh</td>\n","      <td>0.0</td>\n","      <td>lame.</td>\n","      <td>lame.</td>\n","      <td>lame.</td>\n","      <td>how lame.</td>\n","      <td>how lame.</td>\n","    </tr>\n","    <tr>\n","      <th>26053</th>\n","      <td>ohhhh, how sad...i didnï¿½t get it!</td>\n","      <td>sad..</td>\n","      <td>0.0</td>\n","      <td>sad...</td>\n","      <td>sad...</td>\n","      <td>sad...</td>\n","      <td>ohhhh, how sad...</td>\n","      <td>sad...</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                                                                                                       text  ...                             prediction_fold_5\n","9725                                                                                 my tummy hurts...again  ...                                 hurts...again\n","22985                                                          y am i still awake!!!! smh.... this sucks!!!  ...                                      sucks!!!\n","19780                                                       i think my modem failed-having pc withdrawals..  ...                                       failed-\n","3671                             is not feelin well... i feel sooooo weak....i hate bein sick in the summer  ...  is not feelin well... i feel sooooo weak....\n","1149                                                                                but they are expensive.  ...                                    expensive.\n","15735                                                                   i know what you mean  rain sucks...  ...                                 rain sucks...\n","3677                                          migranes suck....especially when the kids are suddenly hyper.  ...                                      suck....\n","9838   is so frustrated!!! i`m stuck at home without any transportation to the global god conference!!! ahh  ...                                 frustrated!!!\n","22948                            srsly, bgt, joke maaan. how lame. ughhhh work tomorah have to get up early  ...                                     how lame.\n","26053                                                                   ohhhh, how sad...i didnï¿½t get it!  ...                                        sad...\n","\n","[10 rows x 8 columns]"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"1MdFuTguTvhL","colab_type":"text"},"source":["# text_tokenCnt"]},{"cell_type":"code","metadata":{"id":"_xQsOn3cTFCg","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":612},"cellView":"form","outputId":"d41b76c6-ffff-46e3-8f02-1cccb699e076","executionInfo":{"status":"ok","timestamp":1590494449614,"user_tz":180,"elapsed":1022451,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","display(k_fold_best[k_fold_best['text_tokenCnt'] <= 3][['text', 'selected_text', \n","                                                        'jaccard_mean', 'prediction_fold_1', \n","                                                        'prediction_fold_2', 'prediction_fold_3', \n","                                                        'prediction_fold_4', 'prediction_fold_5']].sort_values(by=['jaccard_mean']).head(5))\n","\n","display(k_fold_best[k_fold_best['text_tokenCnt'] >= 50][['text', 'selected_text', \n","                                                        'jaccard_mean', 'prediction_fold_1', \n","                                                        'prediction_fold_2', 'prediction_fold_3', \n","                                                        'prediction_fold_4', 'prediction_fold_5']].sort_values(by=['jaccard_mean']).head(5))"],"execution_count":19,"outputs":[{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>jaccard_mean</th>\n","      <th>prediction_fold_1</th>\n","      <th>prediction_fold_2</th>\n","      <th>prediction_fold_3</th>\n","      <th>prediction_fold_4</th>\n","      <th>prediction_fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>25698</th>\n","      <td>me</td>\n","      <td>me</td>\n","      <td>0.0</td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","    </tr>\n","    <tr>\n","      <th>26369</th>\n","      <td>bye.</td>\n","      <td>bye.</td>\n","      <td>0.0</td>\n","      <td>bye</td>\n","      <td>bye</td>\n","      <td>bye</td>\n","      <td>bye</td>\n","      <td>bye</td>\n","    </tr>\n","    <tr>\n","      <th>8766</th>\n","      <td>awww</td>\n","      <td>awww</td>\n","      <td>0.0</td>\n","      <td>a</td>\n","      <td>a</td>\n","      <td>a</td>\n","      <td>a</td>\n","      <td>a</td>\n","    </tr>\n","    <tr>\n","      <th>16641</th>\n","      <td>goodnight!!!</td>\n","      <td>goodnight!!</td>\n","      <td>0.0</td>\n","      <td>goodnight!!!</td>\n","      <td>goodnight!!!</td>\n","      <td>goodnight!!!</td>\n","      <td>goodnight!!!</td>\n","      <td>goodnight!!!</td>\n","    </tr>\n","    <tr>\n","      <th>14338</th>\n","      <td>ow</td>\n","      <td>ow</td>\n","      <td>0.0</td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","      <td></td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["               text selected_text  ...  prediction_fold_4 prediction_fold_5\n","25698            me            me  ...                                     \n","26369          bye.          bye.  ...                bye               bye\n","8766           awww          awww  ...                  a                 a\n","16641  goodnight!!!   goodnight!!  ...       goodnight!!!      goodnight!!!\n","14338            ow            ow  ...                                     \n","\n","[5 rows x 8 columns]"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>jaccard_mean</th>\n","      <th>prediction_fold_1</th>\n","      <th>prediction_fold_2</th>\n","      <th>prediction_fold_3</th>\n","      <th>prediction_fold_4</th>\n","      <th>prediction_fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>21141</th>\n","      <td>grrrr!!! it`s back!!!!! and what i mean is my headache  but on the *       *        bright side....it`s only on one ...</td>\n","      <td>grrrr!!</td>\n","      <td>0.000000</td>\n","      <td>grrrr!!!</td>\n","      <td>grrrr!!! it`s back!!!!! and what i mean is my headache</td>\n","      <td>grrrr!!!</td>\n","      <td>grrrr!!!</td>\n","      <td>grrrr!!!</td>\n","    </tr>\n","    <tr>\n","      <th>8616</th>\n","      <td>brooklyn!!! we went hard!!! now back up top!! but 1st hajji`s...yea again  http://tinyurl.com/codla7 http://ti.. htt...</td>\n","      <td>hard!!</td>\n","      <td>0.000000</td>\n","      <td>hard!!!</td>\n","      <td>hard!!!</td>\n","      <td>hard!!!</td>\n","      <td>we went hard!!!</td>\n","      <td>we went hard!!!</td>\n","    </tr>\n","    <tr>\n","      <th>10091</th>\n","      <td>.ï¿½ï¿½?????ï¿½ï¿½.  i bet. man i wish i coulda went some whr. i didn`t even go out here. i was home all weekend.  n...</td>\n","      <td>nd.  nyt life sux</td>\n","      <td>0.231579</td>\n","      <td>i wish i coulda went some whr. i didn`t even go out here. i was home all weekend.  nyt life sux</td>\n","      <td>sux</td>\n","      <td>sux</td>\n","      <td>sux</td>\n","      <td>sux</td>\n","    </tr>\n","    <tr>\n","      <th>4106</th>\n","      <td>thank a chu?t ï¿½  ch?c v?y quï¿½, hik, ch?c em ph?i ?i h?c 1 khï¿½a ph? c?p ki?n th?c c? khï¿½ g?p =.=</td>\n","      <td>thank a chu?</td>\n","      <td>0.333333</td>\n","      <td>thank</td>\n","      <td>thank</td>\n","      <td>thank</td>\n","      <td>thank</td>\n","      <td>thank</td>\n","    </tr>\n","    <tr>\n","      <th>3746</th>\n","      <td>prayin for dad  in wellington, fl http://loopt.us/f8_jqg.t (via ).  i too live in welly. may i pray f.. http://bit.l...</td>\n","      <td>prayin</td>\n","      <td>0.440000</td>\n","      <td>prayin</td>\n","      <td>prayin for dad  in wellington, fl http://loopt.us/f8_jqg.t (via ).  i too live in welly. may i pray</td>\n","      <td>prayin</td>\n","      <td>prayin for dad  in wellington, fl http://loopt.us/f8_jqg.t (via ).  i too live in welly. may i pray</td>\n","      <td>prayin for dad  in wellington, fl http://loopt.us/f8_jqg.t (via ).  i too live in welly. may i pray</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                                                                                                                          text  ...                                                                                    prediction_fold_5\n","21141  grrrr!!! it`s back!!!!! and what i mean is my headache  but on the *       *        bright side....it`s only on one ...  ...                                                                                             grrrr!!!\n","8616   brooklyn!!! we went hard!!! now back up top!! but 1st hajji`s...yea again  http://tinyurl.com/codla7 http://ti.. htt...  ...                                                                                      we went hard!!!\n","10091  .ï¿½ï¿½?????ï¿½ï¿½.  i bet. man i wish i coulda went some whr. i didn`t even go out here. i was home all weekend.  n...  ...                                                                                                  sux\n","4106                   thank a chu?t ï¿½  ch?c v?y quï¿½, hik, ch?c em ph?i ?i h?c 1 khï¿½a ph? c?p ki?n th?c c? khï¿½ g?p =.=  ...                                                                                                thank\n","3746   prayin for dad  in wellington, fl http://loopt.us/f8_jqg.t (via ).  i too live in welly. may i pray f.. http://bit.l...  ...  prayin for dad  in wellington, fl http://loopt.us/f8_jqg.t (via ).  i too live in welly. may i pray\n","\n","[5 rows x 8 columns]"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"QZqHXjNsTr7B","colab_type":"text"},"source":["# selected_text_tokenCnt"]},{"cell_type":"code","metadata":{"id":"f9RUBZItTawL","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":753},"cellView":"form","outputId":"a540ed66-d61a-49be-bfa9-ae3bdc5dd2a1","executionInfo":{"status":"ok","timestamp":1590494449615,"user_tz":180,"elapsed":1022447,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","print('\\n selected_text_tokenCnt <= 3')\n","display(k_fold_best[k_fold_best['selected_text_tokenCnt'] <= 3][['text', 'selected_text', \n","                                                        'jaccard_mean', 'prediction_fold_1', \n","                                                        'prediction_fold_2', 'prediction_fold_3', \n","                                                        'prediction_fold_4', 'prediction_fold_5']].sort_values(by=['jaccard_mean']).head(5))\n","print('\\n selected_text_tokenCnt >= 50')\n","display(k_fold_best[k_fold_best['selected_text_tokenCnt'] >= 50][['text', 'selected_text', \n","                                                                  'jaccard_mean', 'prediction_fold_1', \n","                                                                  'prediction_fold_2', 'prediction_fold_3', \n","                                                                  'prediction_fold_4', 'prediction_fold_5']].sort_values(by=['jaccard_mean']).head(5))"],"execution_count":20,"outputs":[{"output_type":"stream","text":["\n"," selected_text_tokenCnt <= 3\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>jaccard_mean</th>\n","      <th>prediction_fold_1</th>\n","      <th>prediction_fold_2</th>\n","      <th>prediction_fold_3</th>\n","      <th>prediction_fold_4</th>\n","      <th>prediction_fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>13226</th>\n","      <td>you guys were absolutely amazing tonight, as always. thanks for always bringing the dance party.</td>\n","      <td>ly amazin</td>\n","      <td>0.0</td>\n","      <td>you guys were absolutely amazing</td>\n","      <td>amazing</td>\n","      <td>amazing</td>\n","      <td>amazing</td>\n","      <td>you guys were absolutely amazing</td>\n","    </tr>\n","    <tr>\n","      <th>26427</th>\n","      <td>**** that is awful... could not believe it at first... so sad</td>\n","      <td>awful.</td>\n","      <td>0.0</td>\n","      <td>**** that is awful...</td>\n","      <td>**** that is awful...</td>\n","      <td>**** that is awful...</td>\n","      <td>**** that is awful...</td>\n","      <td>**** that is awful...</td>\n","    </tr>\n","    <tr>\n","      <th>18772</th>\n","      <td>give them my best!</td>\n","      <td>y best</td>\n","      <td>0.0</td>\n","      <td>best!</td>\n","      <td>best!</td>\n","      <td>best!</td>\n","      <td>best!</td>\n","      <td>best!</td>\n","    </tr>\n","    <tr>\n","      <th>22450</th>\n","      <td>cool!!! no wonder you didn`t sleep much</td>\n","      <td>cool!</td>\n","      <td>0.0</td>\n","      <td>cool!!!</td>\n","      <td>cool!!!</td>\n","      <td>cool!!!</td>\n","      <td>cool!!!</td>\n","      <td>cool!!!</td>\n","    </tr>\n","    <tr>\n","      <th>12521</th>\n","      <td>saying goodbye to a good trusted friend today. goodbye free sky tv, you were the best friend anyone could have had.</td>\n","      <td>goodb</td>\n","      <td>0.0</td>\n","      <td>you were the best friend anyone could have had.</td>\n","      <td>you were the best friend anyone could have had.</td>\n","      <td>good trusted friend today. goodbye free sky tv, you were the best friend anyone could have had.</td>\n","      <td>good trusted friend today. goodbye free sky tv, you were the best friend anyone could have had.</td>\n","      <td>good trusted friend today. goodbye free sky tv, you were the best friend anyone could have had.</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                                                                                                                      text  ...                                                                                prediction_fold_5\n","13226                     you guys were absolutely amazing tonight, as always. thanks for always bringing the dance party.  ...                                                                 you guys were absolutely amazing\n","26427                                                        **** that is awful... could not believe it at first... so sad  ...                                                                            **** that is awful...\n","18772                                                                                                   give them my best!  ...                                                                                            best!\n","22450                                                                              cool!!! no wonder you didn`t sleep much  ...                                                                                          cool!!!\n","12521  saying goodbye to a good trusted friend today. goodbye free sky tv, you were the best friend anyone could have had.  ...  good trusted friend today. goodbye free sky tv, you were the best friend anyone could have had.\n","\n","[5 rows x 8 columns]"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"," selected_text_tokenCnt >= 50\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>jaccard_mean</th>\n","      <th>prediction_fold_1</th>\n","      <th>prediction_fold_2</th>\n","      <th>prediction_fold_3</th>\n","      <th>prediction_fold_4</th>\n","      <th>prediction_fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>24998</th>\n","      <td>????  ? ??????, ?????? ????????,basquash,k-on,07-ghost,sengoku basara,valkyria chronicles,requiemforthephantom,edeno...</td>\n","      <td>????  ? ??????, ?????? ????????,basquash,k-on,07-ghost,sengoku basara,valkyria chronicles,requiemforthephantom,edeno...</td>\n","      <td>0.633333</td>\n","      <td>???  ? ??????, ?????? ????????,basquash,k-on,07-ghost,sengoku basara,valkyria chronicles,requiemforthephantom,edenof...</td>\n","      <td>???  ? ??????, ?????? ????????,basquash,k-on,07-ghost,sengoku basara,valkyria chronicles,requiemforthephantom,edenof...</td>\n","      <td>???  ? ??????, ?????? ????????,basquash,k-on,07-ghost,sengoku basara,valkyria chronicles,requiemforthephantom,edenof...</td>\n","      <td>???  ? ??????, ?????? ????????,basquash,k-on,07-ghost,sengoku basara,valkyria chronicles,requiemforthephantom,edenof...</td>\n","      <td>???  ? ??????, ?????? ????????,basquash,k-on,07-ghost,sengoku basara,valkyria chronicles,requiemforthephantom,edenof...</td>\n","    </tr>\n","    <tr>\n","      <th>3292</th>\n","      <td>legend of inotia ??????? ??????. ?????? ???????. ???? ??????? 31? ?????, ????? ?????? ???. ????????? ???? ?????? ???...</td>\n","      <td>legend of inotia ??????? ??????. ?????? ???????. ???? ??????? 31? ?????, ????? ?????? ???. ????????? ???? ?????? ???...</td>\n","      <td>0.685714</td>\n","      <td>legend of inotia</td>\n","      <td>legend of inotia</td>\n","      <td>legend of inotia ??????? ??????. ?????? ???????. ???? ??????? 31? ?????, ????? ?????? ???. ????????? ???? ?????? ???...</td>\n","      <td>legend of inotia ??????? ??????. ?????? ???????. ???? ??????? 31? ?????, ????? ?????? ???. ????????? ???? ?????? ???...</td>\n","      <td>legend of inotia</td>\n","    </tr>\n","    <tr>\n","      <th>15551</th>\n","      <td>yï¿½n tï¿½m, sang n?m s? th?y **** m?c tr?n tinh twitter tr? l?i lï¿½ thï¿½ng , th?ch sanh nh? lï¿½m quiz mï¿½ c??i ...</td>\n","      <td>yï¿½n tï¿½m, sang n?m s? th?y **** m?c tr?n tinh twitter tr? l?i lï¿½ thï¿½ng , th?ch sanh nh? lï¿½m quiz mï¿½ c??i ...</td>\n","      <td>0.687179</td>\n","      <td>yï¿½n tï¿½m, sang n?m s? th?y **** m?c tr?n tinh twitter tr? l?i lï¿½ thï¿½ng</td>\n","      <td>yï¿½n tï¿½m, sang n?m s? th?y **** m?c tr?n tinh twitter tr? l?i lï¿½ thï¿½ng , th?ch sanh nh?</td>\n","      <td>yï¿½n tï¿½m, sang n?m s? th?y **** m?c tr?n tinh twitter tr? l?i lï¿½ thï¿½ng , th?ch sanh nh</td>\n","      <td>yï¿½n tï¿½m, sang n?m s? th?y **** m?c tr?n tinh twitter tr? l?i lï¿½ thï¿½ng , th?ch sanh nh?</td>\n","      <td>yï¿½n tï¿½m, sang n?m s? th?y **** m?c tr?n tinh twitter tr? l?i lï¿½ thï¿½ng , th?ch sanh nh</td>\n","    </tr>\n","    <tr>\n","      <th>27317</th>\n","      <td>just saw an advert for attics to eden on tv  out today and only ï¿½9.99 from hmv...so i`m not sure why i had to pay ...</td>\n","      <td>just saw an advert for attics to eden on tv  out today and only ï¿½9.99 from hmv...so i`m not sure why i had to pay ...</td>\n","      <td>0.978571</td>\n","      <td>just saw an advert for attics to eden on tv  out today and only ï¿½9.99 from hmv...so i`m not sure why i had to pay ...</td>\n","      <td>just saw an advert for attics to eden on tv  out today and only ï¿½9.99 from hmv...so i`m not sure why i had to pay ...</td>\n","      <td>just saw an advert for attics to eden on tv  out today and only ï¿½9.99 from hmv...so i`m not sure why i had to pay ...</td>\n","      <td>just saw an advert for attics to eden on tv  out today and only ï¿½9.99 from hmv...so i`m not sure why i had to pay ...</td>\n","      <td>just saw an advert for attics to eden on tv  out today and only ï¿½9.99 from hmv...so i`m not sure why i had to pay ...</td>\n","    </tr>\n","    <tr>\n","      <th>1586</th>\n","      <td>link per my daughter  us.mobile.reuters.com/mobile/m/anyarticle/p.rdt?url=http://www.reuters.com/article/bigmoney/id...</td>\n","      <td>link per my daughter  us.mobile.reuters.com/mobile/m/anyarticle/p.rdt?url=http://www.reuters.com/article/bigmoney/id...</td>\n","      <td>1.000000</td>\n","      <td>link per my daughter  us.mobile.reuters.com/mobile/m/anyarticle/p.rdt?url=http://www.reuters.com/article/bigmoney/id...</td>\n","      <td>link per my daughter  us.mobile.reuters.com/mobile/m/anyarticle/p.rdt?url=http://www.reuters.com/article/bigmoney/id...</td>\n","      <td>link per my daughter  us.mobile.reuters.com/mobile/m/anyarticle/p.rdt?url=http://www.reuters.com/article/bigmoney/id...</td>\n","      <td>link per my daughter  us.mobile.reuters.com/mobile/m/anyarticle/p.rdt?url=http://www.reuters.com/article/bigmoney/id...</td>\n","      <td>link per my daughter  us.mobile.reuters.com/mobile/m/anyarticle/p.rdt?url=http://www.reuters.com/article/bigmoney/id...</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                                                                                                                          text  ...                                                                                                        prediction_fold_5\n","24998  ????  ? ??????, ?????? ????????,basquash,k-on,07-ghost,sengoku basara,valkyria chronicles,requiemforthephantom,edeno...  ...  ???  ? ??????, ?????? ????????,basquash,k-on,07-ghost,sengoku basara,valkyria chronicles,requiemforthephantom,edenof...\n","3292   legend of inotia ??????? ??????. ?????? ???????. ???? ??????? 31? ?????, ????? ?????? ???. ????????? ???? ?????? ???...  ...                                                                                                         legend of inotia\n","15551  yï¿½n tï¿½m, sang n?m s? th?y **** m?c tr?n tinh twitter tr? l?i lï¿½ thï¿½ng , th?ch sanh nh? lï¿½m quiz mï¿½ c??i ...  ...                            yï¿½n tï¿½m, sang n?m s? th?y **** m?c tr?n tinh twitter tr? l?i lï¿½ thï¿½ng , th?ch sanh nh\n","27317  just saw an advert for attics to eden on tv  out today and only ï¿½9.99 from hmv...so i`m not sure why i had to pay ...  ...  just saw an advert for attics to eden on tv  out today and only ï¿½9.99 from hmv...so i`m not sure why i had to pay ...\n","1586   link per my daughter  us.mobile.reuters.com/mobile/m/anyarticle/p.rdt?url=http://www.reuters.com/article/bigmoney/id...  ...  link per my daughter  us.mobile.reuters.com/mobile/m/anyarticle/p.rdt?url=http://www.reuters.com/article/bigmoney/id...\n","\n","[5 rows x 8 columns]"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"KxVQX4P5UTLP","colab_type":"text"},"source":["# Jaccard histogram"]},{"cell_type":"code","metadata":{"id":"Cg2fk31aUUyH","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":351},"cellView":"form","outputId":"34668e54-604b-46bb-99fa-800e077697ff","executionInfo":{"status":"ok","timestamp":1590494450237,"user_tz":180,"elapsed":1023064,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","fig, ax = plt.subplots(1, 1, figsize=(20, 5))\n","sns.distplot(k_fold_best['jaccard_mean'], ax=ax).set_title(f\"Overall 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\n","text/plain":["<Figure size 1440x360 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"vrdkYGfi-K60","colab_type":"text"},"source":["## By sentiment"]},{"cell_type":"code","metadata":{"id":"C2z6O4ORUi6A","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":894},"cellView":"form","outputId":"268beb35-72a5-48e7-9562-8189191e4811","executionInfo":{"status":"ok","timestamp":1590494450828,"user_tz":180,"elapsed":1023647,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(20, 15), sharex=False)\n","sns.distplot(k_fold_best[k_fold_best['sentiment'] == 'neutral']['jaccard_mean'], ax=ax1).set_title(f\"Neutral [{len(k_fold_best[k_fold_best['sentiment'] == 'neutral'])}]\")\n","sns.distplot(k_fold_best[k_fold_best['sentiment'] == 'positive']['jaccard_mean'], ax=ax2).set_title(f\"Positive [{len(k_fold_best[k_fold_best['sentiment'] == 'positive'])}]\")\n","sns.distplot(k_fold_best[k_fold_best['sentiment'] == 'negative']['jaccard_mean'], ax=ax3).set_title(f\"Negative [{len(k_fold_best[k_fold_best['sentiment'] == 'negative'])}]\")\n","sns.despine()\n","plt.show()"],"execution_count":22,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1440x1080 with 3 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"FR8x4hYY-NI0","colab_type":"text"},"source":["## By text token count"]},{"cell_type":"code","metadata":{"id":"XzLl3cYqVFFa","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":622},"cellView":"form","outputId":"e7718ab5-ee94-476e-c2f5-c7f79b68354e","executionInfo":{"status":"ok","timestamp":1590494452029,"user_tz":180,"elapsed":1024839,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(20, 10), sharex=False)\n","sns.distplot(k_fold_best[k_fold_best['text_tokenCnt'] <= 3]['jaccard_mean'], ax=ax1).set_title(f\"text_tokenCnt <= 3 [{len(k_fold_best[k_fold_best['text_tokenCnt'] <= 3])}]\")\n","sns.distplot(k_fold_best[k_fold_best['text_tokenCnt'] >= 50]['jaccard_mean'], ax=ax2).set_title(f\"text_tokenCnt >= 50 [{len(k_fold_best[k_fold_best['text_tokenCnt'] >= 50])}]\")\n","sns.despine()\n","plt.show()"],"execution_count":23,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1440x720 with 2 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"iwoue1xw-PQo","colab_type":"text"},"source":["## By selected_text token count"]},{"cell_type":"code","metadata":{"id":"9kJIizCKVE8v","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":622},"cellView":"form","outputId":"afdb8939-f2c3-468a-f4ae-d3ca7bc1a6f1","executionInfo":{"status":"ok","timestamp":1590494452032,"user_tz":180,"elapsed":1024836,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["#@title\n","fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(20, 10), sharex=False)\n","sns.distplot(k_fold_best[k_fold_best['selected_text_tokenCnt'] <= 3]['jaccard_mean'], ax=ax1).set_title(f\"selected_text_tokenCnt <= 3 [{len(k_fold_best[k_fold_best['selected_text_tokenCnt'] <= 3])}]\")\n","sns.distplot(k_fold_best[k_fold_best['selected_text_tokenCnt'] >= 50]['jaccard_mean'], ax=ax2).set_title(f\"selected_text_tokenCnt >= 50 [{len(k_fold_best[k_fold_best['selected_text_tokenCnt'] >= 50])}]\")\n","sns.despine()\n","plt.show()"],"execution_count":24,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAABIEAAAJdCAYAAAClGmevAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nOzdeZhcZZ328ftXa+/7kqSTTmchBBJCEgJhUwQHBRQYdwFZZFMU5nUYx2VmHGXG7dVxGMfxBTOIgCwqbqAoiis7JIQEAkmA7El3kt737tqe949zutNpOqETqlPdXd/PddV1Tp3lOU9VTpKqu57FnHMCAAAAAADA5BbIdAUAAAAAAAAw9giBAAAAAAAAsgAhEAAAAAAAQBYgBAIAAAAAAMgChEAAAAAAAABZgBAIAAAAAAAgCxACAQAAAAAAZAFCIAAAJgAzqzMzZ2ahDNfjS2Z2dybrkC5mdoWZPZ7pekx0ZrbVzHrN7IfjoC43mVn3ePi7AgDAeEQIBABAFvG/sP/NGF8jbYHVoZQ1nkIdM3unmT1qZp1m1mhmfzWzC0Z57l/M7OqxruNBrn+sma0ys1b/8QczO/YNTjvfOXfpkDJONbNn/df/gpmdPmTf28wsZWZdQx6XD9l/jJn9yczazew1M3vPkH2XDDuvx78/TpAk59wXJS1I37sBAMDkQggEAACQRmb2fkn3S7pL0nRJ1ZL+VdL5R+DaZmaVb7KYeknvl1QmqULSg5J+dAh1KJP0K0nflFQi6RuSfmVmpUOv4ZwrGPK40z83JOkBSb/2r3+tpLvNbJ4kOefuGXqepE9I2ixp9Zt6xQAAZAlCIAAAjjAz+6yZ7fJbSWw0s7f72wNm9jkz22RmzWb2E/8L9UhlFJvZ982swS/ry2YWHLL/GjNb71/jZTNb6nfXqZX3hbzLzD7jH3uymT1pZm1mttbM3jaknFl+K5ZOM3tEXijwRh71l23+dU7xy7rSr1Ormf3OzGYOeT+eGWjtY2bXmdlLZpZzoLJGeD+OkXSrpFP849qGvE93+a1xtpnZv5jZiJ9/zOybZva4f84B39+BFkdm9h/+a9liZuf6+0zSf0r6d+fcbc65dudcyjn3V+fcNaM4/yuS3iLpf/zX8T+jeL9lZrPN7CZJWyRdOZpzDsQ51+ac2+qcc5JMUlLS3EMo4lRJu51z9zvnks65uyU1SnrvKM6dL2mapJv9c/8k6QlJlx7g+Msl3eXXFQAAvAFCIAAAjiAzO1rS9ZJOdM4VSnqnpK3+7hsk/a2kM+R9EW6V9N0DFHWHpIS8L+dLJL1D0tX+NT4g6UuSLpNUJOkCSc1+d53t8rruFDjnvmFmNZIekvRleS0vPi3pZ0Nak9wr6Tl54c+/y/vS/Ube6i9L/Os8ZWYXSvoneUFApaTHJN3nH/dNSf2S/sXMjpL0VUkfcc71jVTWSBd0zq2X9HFJT/nHlfi7viOpWNJsee/rZZI+OvRcP3z7X0mLJL3DOdeug7y/vuWSNvrvyzckfd8PgI6WNEPST9/gPRrxfOfcP/vvzfX+67j+QAWYWZ6ZXWZmf5a0UlKVpA855/7vkGPaDvL43MEq6AdpffLew6++wet53ekjPF845HmVme3xA7CbzSz/Dcpa+LqNXoj4VnktrgAAwCgQAgEAcGQlJUUlHWtmYb/FxSZ/38cl/bNzbqdzrl9ekPN+GzYejplVSzpP0qecc93Oub2Sbpb0Yf+QqyV9wzm30nlec85tO0B9PiLpN8653/gtVh6RtErSeWZWK+lESV9wzvU75x6V183ncHxc0tecc+udcwl5ocJiM5vpnEvJC2f+Tl7Xo284554/zOsM8lvufFjS551znc65rZK+pf1blYTlhVFl8sKxnlG8v5K0zTn3v865pKQ7JU2V1+2r3N/f8AbVO9D5o31tt0na6dfpFknTnHPXOeeeGXqcc67kII+vH+wafpBWLC+0PJQ/j6ckTTOzi8wsbN54P3Mk5fn7N0haLO81nyXpBHmtpyQvGNsr6R/9c98hL7zL0+tdJukx59yWQ6gbAABZjRAIAIAjyDn3mqRPyQt49prZj8xsmr97pqRfDLTUkLReXmg0PByYKS+8aBhy7PfktQSRvJYomzQ6MyV9YGgLEUmny/uCPk1Sq3Oue8jxBwqTRnOdbw+5Rou8Fh41kuQHNH+WVKcDt346VBXy3qehdd42cE3fXEkXSrrJORcbUteDvb+StHtgxTnX468WSGr216e+Qd0OdP5oLZQUk7RG0gt+aJh2/p/9rZLuMrOqNzreP6dZ3nt6o6Q9ks6R9Ad5oZWcc7udcy/7oeMWSZ+R9D5/X1xea7h3yXuP/kHSTwbOHeYyeQEaAAAYJUIgAACOMOfcvc650+WFDU7SQPedHZLOHdZaI8c5t2tYETvkdZ+qGHJckXNuwZD9cw50+RHK+uGwa+b7rUQaJJUO66pTO5qXOMK2HZI+Nuw6uc65JyXJzN4l6RRJf5TXPexgZY32uk2S4vLe5wG1koa+n+vldQ/7rd9Vb6CuB3t/D2ajf/77DqHew73ha3bOnSzpTEkhSX8ybyau682sfOhxtv9MWsMf/zTK+gTktcSpeaMDh9Tvr865E51zZfJaXs2X9OyBDteQz6TOuRecc2c458qdc++U15Vvv3PN7DR5IeUbdbsDAABDEAIBAHAEmdnRZnaWmUXljbfSKynl775V0leGDJhc6Y+lsx/nXIOk30v6lpkV+WPazDGzM/xDbpP0aTM7wTxzB8qU1zJj9pDi7pZ0vnlTmgfNLMe8Kbyn+13IVkm6ycwi5k3zPZoZrhr91zT0OrdK+ryZLfBfW7E/dpHMrMKv89Xyxhw638zOO0hZB7JH0nQzi/jvU1JeK5KvmFmh/x7c6L/mQc65++SNV/QHM5szivf3gPwBim+U9AUz++iQ8083sxWjeA0Dr+MNX6/fte4z8lp+3SSv29RWM7tqyDEFB3mMOM6PmZ1tZkv8+6FIXletVnmB2aj454f98/9D0g7n3O/8fWea2Uz/3pwh6evyZgQbOHeRfx/mmdmn5bWqumPYJS6X9DPnXOdo6wQAAAiBAAA40qLyvvQ2yevuUiXp8/6+b8sbE+f3ZtYp6Wl5AwiP5DJJEUkvy/uC/lP5XZCcc/dL+oq8QZ07Jf1S3pg3kvQ1eQMwt5nZp51zO+R13fkneYHLDkn/qH2fES7269Ai6YsaxSC8fvemr0h6wr/Oyc65X8hr8fQjM+uQtE7Suf4pKyQ94I9L1CzpKkm3mVn5SGUd5NJ/kvSSpN1m1uRvu0FSt7xpxB/335PbR6jznZL+TV6rmjod5P0dxev/qaQPyZulq15eqPNlDQk63sC35Y0F1Wpm/z2K6yWdcw855z4gr9XTiINnH4ISeeMktcvrVjhH0jnOG6h7tD4j7x7fIe99e8+QfUskPSnvz+VJSS/KGw9qwKXyWqHtlfR2SWcP7e5m3qxxHxRdwQAAOGTmmFETAAAAh8nMNsoLen7hnBvN7HFjWZcvymuJFZWU77cGAwAAPkIgAAAAAACALEB3MAAAcMjM7JIDDDb80hhf99YDXPfWsbwuAADAZEBLIAAAAAAAgCwQytSFzznnHPfwww9n6vIAAAAAAACTkR1oR8a6gzU1Nb3xQQAAAAAAAEgLxgQCAAAAAADIAoRAAAAAAAAAWYAQCAAAAAAAIAsQAgEAAAAAAGQBQiAAAAAAAIAsQAgEAAAAAACQBQiBAAAAAAAAsgAhEAAAAAAAQBYgBAIAAAAAAMgCaQuBzOxoM1sz5NFhZp9KV/kAAAAAAAA4fKF0FeSc2yhpsSSZWVDSLkm/SFf5AAAAAICJ495ntme6CqNy8fLaTFcBOGLGqjvY2yVtcs5tG6PyAQAAAAAAcAjGKgT6sKT7hm80s2vNbJWZrWpsbByjSwMAAAAAAGC4tIdAZhaRdIGk+4fvc86tcM4tc84tq6ysTPelAQAAAAAAcABj0RLoXEmrnXN7xqBsAAAAAAAAHIaxCIEu0ghdwQAAAAAAAJA5aQ2BzCxf0tmSfp7OcgEAAAAAAPDmpG2KeElyznVLKk9nmQAAAAAAAHjzxmp2MAAAAAAAAIwjhEAAAAAAAABZgBAIAAAAAAAgCxACAQAAAAAAZAFCIAAAAAAAgCxACAQAAAAAAJAFCIEAAAAAAACyACEQAAAAAABAFiAEAgAAAAAAyAKEQAAAAAAAAFmAEAgAAAAAACALEAIBAAAAAABkAUIgAAAAAACALEAIBAAAAAAAkAUIgQAAAAAAALIAIRAAAAAAAEAWIAQCAAAAAADIAoRAAAAAAAAAWYAQCAAAAAAAIAsQAgEAAAAAAGQBQiAAAAAAAIAsQAgEAAAAAACQBQiBAAAAAAAAsgAhEAAAAAAAQBZIawhkZiVm9lMz22Bm683slHSWDwAAAAAAgMMTSnN535b0sHPu/WYWkZSX5vIBAAAAAABwGNIWAplZsaS3SrpCkpxzMUmxdJUPAAAAAACAw5fO7mCzJDVK+oGZPW9mt5lZ/tADzOxaM1tlZqsaGxvTeGkAAAAAAAAcTDpDoJCkpZJucc4tkdQt6XNDD3DOrXDOLXPOLausrEzjpQEAAAAAAHAw6QyBdkra6Zx7xn/+U3mhEAAAAAAAADIsbSGQc263pB1mdrS/6e2SXk5X+QAAAAAAADh86Z4d7AZJ9/gzg22W9NE0lw8AAAAAAIDDkNYQyDm3RtKydJYJAAAAAACANy+dYwIBAAAAAABgnCIEAgAAAAAAyAKEQAAAAAAAAFmAEAgAAAAAACALEAIBAAAAAABkAUIgAAAAAACALEAIBAAAAAAAkAUIgQAAAAAAALIAIRAAAAAAAEAW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\n","text/plain":["<Figure size 1440x720 with 2 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]}]}