Statistical Learning from a Regression Perspective (Springer Series in Statistics) Pdf

Book Detail
Edition: 2008
Release: 2008-07-31
Publisher: Springer
Binding: Hardcover
ISBN/ASIN: 0387775005
Format: hardcover, kindle, PDF, EPUB

Statistical Learning from a Regression Perspective (Springer Series in Statistics) pdf
Description

Statistical Learning from a Regression Perspective considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important to characterize how the predictors are related to the response. As a first approximation, this is can be seen as an extension of nonparametric regression. Among the statistical learning procedures examined are bagging, random forests, boosting, and support vector machines. Response variables may be quantitative or categorical. Real applications are emphasized, especially those with practical implications. One important theme is the need to explicitly take into account asymmetric costs in the fitting process. For example, in some situations false positives may be far less costly than false negatives. Another important theme is to not automatically cede modeling decisions to a fitting algorithm. In many settings, subject-matter knowledge should trump formal fittin Download Statistical Learning from a Regression Perspective (Springer Series in Statistics) for free via rapidshare, mediafire, 4shared, dropBox, uploading, fileserve

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