An Introduction to Statistical Learning 2025 pdf epub mobi 電子書下載

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An Introduction to Statistical Learning pdf epub mobi 著者簡介

Gareth James is a professor of data sciences and operations at the University of Southern California. He has published an extensive body of methodological work in the domain of statistical learning with particular emphasis on high-dimensional and functional data. The conceptual framework for this book grew out of his MBA elective courses in this area.

Daniela Witten is an associate professor of statistics and biostatistics at the University of Washington. Her research focuses largely on statistical machine learning in the high-dimensional setting, with an emphasis on unsupervised learning.

Trevor Hastie and Robert Tibshirani are professors of statistics at Stanford University, and are co-authors of the successful textbook Elements of Statistical Learning. Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap.

An Introduction to Statistical Learning pdf epub mobi 圖書描述

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

An Introduction to Statistical Learning 2025 pdf epub mobi 電子書下載

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An Introduction to Statistical Learning 2025 pdf epub mobi 電子書下載

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1. expected test MSE use：to assess the accuracy of model predictions. obtain: repeatedly estimate f using a large number of training sets and test each at x0. decompose: into 3 parts -- variance, bias and irreducible error. note: the meaning of variance an...

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1，統計學習的入門書，通俗易懂，號稱是ESL的入門版，全書沒有太多數學推導，適閤學工程的人不適閤學統計的人讀。2，監督學習占瞭大部分篇幅，我覺得這本書最好的部分就是模型的討論都圍繞variance和bias的trade-off展開，還有就是對模型的整體性能，以及參數的經驗取值都給齣...

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http://www-bcf.usc.edu/~gareth/ISL/ ==========================================================================================================================================================

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Notes of Introduction to Statistical Learning ===================================== ## Statistical Learning - basic concepts - two main reasons to estimate f: prediction and inference - trade-off: complex models may be good for accurate prediction, but it m...

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出版者:Springer

作者:Gareth James

出品人:

頁數:426

譯者:

出版時間:2013-8-12

價格:USD 79.99

裝幀:Hardcover

isbn號碼:9781461471370

叢書系列:Springer Texts in Statistics