Titlebook: An Introduction to Statistical Learning; with Applications in Gareth James,Daniela Witten,Robert Tibshirani Textbook 2021Latest edition The

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https://doi.org/10.1007/978-3-8349-8760-0Most of this book concerns . methods such as regression and classification. In the supervised learning setting, we typically have access to a set of . features . measured on . observations, and a response . also measured on those same . observations. The goal is then to predict . using

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Classification,The linear regression model discussed in Chap. . assumes that the response variable . is quantitative. But in many situations, the response variable is instead ..

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Resampling Methods, are an indispensable tool in modern statistics. They involve repeatedly drawing samples from a training set and refitting a model of interest on each sample in order to obtain additional information about the fitted model.

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Linear Model Selection and Regularization,In the regression setting, the standard linear model .is commonly used to describe the relationship between a response Y and a set of variables ., .,…,..