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Twin Bounded Least Squares Support Vector Regression
Support Vector Machine (SVM) has received much attention in machine learning due to its profound theoretical research and practical application...
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Projection generalized correntropy twin support vector regression
A projection generalized maximum correntropy twin support vector regression algorithm is proposed. The generalized correntropy function is added into...
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Foretelling the compressive strength of concrete using twin support vector regression
Characteristic compressive strength is a key and crucial physical attribute of concrete used in various design standards and rules. In this study,...
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Gradient Descent for Hyperparameter Selection in Least Squares Support Vector Regression
Hyperparameter selection, an important and challenging problem in machine learning, is particularly crucial for achieving optimal performance. Least...
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Fractional-order least squares support vector regression to solve left-sided Bessel fractional pantograph differential equations
This study presents a machine learning approach using least squares support vector regression (LS-SVR) for solving fractional pantograph differential...
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Optimized support vector regression predicting treatment duration among tuberculosis patients in Malaysia
Machine learning models have emerged as an advanced tool for predicting diseases and their outcomes. This study developed a machine learning model to...
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Robust twin support vector regression with correntropy-based metric
Machine learning methods have been widely used control and information systems. Robust learning is an important issue in machine learning field. In...
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Carbon prices forecasting based on sliding time window and improved support vector regression
Carbon emission trading system is one of the important means for China to tackle climate warming and achieve the dual-carbon goals. However, due to...
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The improved mountain gazelle optimizer for spatiotemporal support vector regression: a novel method for railway subgrade settlement prediction integrating multi-source information
The uneven settlement of railway subgrades not only affects the comfort of train operations but, in extreme cases, may compromise operational safety....
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Twin Support Vector Regression with Privileged Information
In this paper, we propose a novel framework called Twin Support Vector Regression with Privileged Information (TSVR+), which aims to improve the...
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Optimizing support vector regression using grey wolf optimizer for enhancing energy efficiency and building prototype architecture
In this era of increasing energy demand, optimizing energy consumption in building systems is critical for enhancing sustainability and operational...
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Support Vector Machine
This chapter provides a comprehensive overview of support vector machines (SVM), a critical algorithm in classification and regression analysis. It...
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Support Vector Machines – An Introduction
This is a book about learning from empirical data (i.e., examples, samples, measurements, records, patterns or observations) by applying support...
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An Optimal Topic Centric Crawler for Acquiring Bio-medical Themes Utilizing Gaussian Support Vector Regression
Focused crawler (FC) is a web crawler that downloads only relevant web pages for a given topic. The main source of biomedical information is now the...
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Fuzzy Support Vector Machines with Automatic Membership Setting
Support vector machines like other classification approaches aim to learn the decision surface from the input points for classification problems or...
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Gas Sensing Using Support Vector Machines
In this chapter we deal with the use of Support Vector Machines in gas sensing. After a brief introduction to the inner workings of multisensor...
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An Efficient Mobile Edge Computing based Resource Allocation using Optimal Double Weighted Support Vector Transfer Regression
Mobile edge computing (MEC) technology is gaining more attention in smart cities due to its powerful computation capability. However, there arise...
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A novel hybrid PSO- and GS-based hyperparameter optimization algorithm for support vector regression
Hyperparameter optimization is vital in improving the prediction accuracy of support vector regression (SVR), as in all machine learning algorithms....
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Componentwise Least Squares Support Vector Machines
This chapter describes componentwise Least Squares Support Vector Machines (LS-SVMs) for the estimation of additive models consisting of a sum of...
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Robust Twin Support Vector Regression with Smooth Truncated Hε Loss Function
Twin support vector regression (TSVR) is an important algorithm to handle regression problems developed on the basis of support vector regression...
