Titlebook: Statistical Learning from a Regression Perspective; Richard A. Berk Textbook 2020Latest edition Springer Nature Switzerland AG 2020 classi

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Statistical Learning as a Regression Problem,regression model; (2) different forms of regression analysis are properly viewed as approximations of the true relationships, which is a game changer; (3) statistical learning can be just another kind of regression analysis; (4) and properly formulated regression approximations can have asymptotical

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Splines, Smoothers, and Kernels,ibutions. How does the conditional mean or conditional proportion vary with different predictor values? The intent is to begin with procedures that have much the same look and feel as conventional linear regression and gradually move toward procedures that do not. Many of the procedures can be viewe

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Classification and Regression Trees (CART),T). We will see that the algorithmic machinery successively subsets the data. Trees are just a visualization of the data subsetting processes. We will also see that although recursive partitioning has too many problems to be an effective, stand-alone data analysis procedure, it is a crucial componen

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Bagging,ted values. These are often unstable and subject to a painful bias – variance tradeoff. In this chapter, we turn to what some call “ensemble” algorithms which can produce many sets of fitted values. These, in turn, can be averaged in a manner that reduces instability, often with no increase in the b

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Boosting,cal learning procedure makes many passes through the data and constructs fitted values for each. However, with each pass, observations that were fit more poorly on the last pass are given more weight. In that way, the algorithm works more diligently to fit the hard-to-fit observations. In the end, e

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Support Vector Machines,that maximizes a somewhat different definition of a margin, which leads to a novel “hinge” loss function. Also distinctive is the use of kernels in place of the usual design matrix. The kernels allow for very complicated linear basis expansions derived from the full set of predictors. Support vector

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Textbook 2020Latest editionsalient, tensions that result. Throughout, there are links to the big picture...The third edition considers significant advances in recent years, among which are:..the development of overarching, conceptual frameworks for statistical learning;.the impact of  “big data” on statistical learning;.the n