Abstract
Most of this book concerns supervised learning methods such as regression and classification. In the supervised learning setting, we typically have access to a set of p features \( X_{1}, X_{2}, \ldots, X_{p},\) measured on n observations, and a response Y also measured on those same n observations. The goal is then to predict Y using \( X_{1}, X_{2}, \ldots, X_{p}.\)
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James, G., Witten, D., Hastie, T., Tibshirani, R. (2021). Unsupervised Learning. In: An Introduction to Statistical Learning. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-0716-1418-1_12
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DOI: https://doi.org/10.1007/978-1-0716-1418-1_12
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