28、Support Vector Machines and Cohen‘s d Calculation in Machine Learning

Support Vector Machines and Cohen’s d Calculation in Machine Learning

1. Introduction to Support Vector Machines (SVM)

Support vector machines (SVM) and random forests are fundamental techniques in machine learning. Although they don’t offer a straightforward and easily understandable model, they are highly effective for predicting continuous variables and classifying categorical ones.

1.1 SVM Basics

SVM can be used for both regression and classification problems. In classification, when dealing with a dichotomous variable (y) representing two groups and a set of explanatory variables (X), SVM, along with discriminant analysis and logistic regression, aims to find the equation of a separating hyperplane. This hyperplane is a linear combinat