The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

Robert Tibshirani


During the earlier decade there was an explosion in computation and data know-how. With it have come big quantities of knowledge in quite a few fields comparable to drugs, biology, finance, and advertising. The problem of knowing those info has ended in the advance of recent instruments within the box of information, and spawned new components equivalent to facts mining, desktop studying, and bioinformatics. a lot of those instruments have universal underpinnings yet are frequently expressed with assorted terminology. This publication describes the real rules in those components in a typical conceptual framework. whereas the method is statistical, the emphasis is on techniques instead of arithmetic. Many examples are given, with a liberal use of colour snap shots. It is a invaluable source for statisticians and an individual attracted to info mining in technological know-how or undefined. The book's insurance is wide, from supervised studying (prediction) to unsupervised studying. the various issues contain neural networks, aid vector machines, category timber and boosting---the first entire remedy of this subject in any book.

This significant re-creation positive factors many subject matters no longer lined within the unique, together with graphical versions, random forests, ensemble tools, least perspective regression & direction algorithms for the lasso, non-negative matrix factorization, and spectral clustering. there's additionally a bankruptcy on equipment for ``wide'' facts (p larger than n), together with a number of trying out and fake discovery rates.

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