By Trevor Hastie
Up to now decade there was an explosion in computation and data know-how. With it have come substantial quantities of knowledge in numerous fields equivalent to drugs, biology, finance, and advertising. The problem of knowing those information has ended in the improvement of latest instruments within the box of information, and spawned new parts similar to info mining, computing device studying, and bioinformatics. lots of those instruments have universal underpinnings yet are usually expressed with diverse terminology. This booklet describes the $64000 principles in those parts in a typical conceptual framework. whereas the method is statistical, the emphasis is on suggestions instead of arithmetic. Many examples are given, with a liberal use of colour snap shots. it's a invaluable source for statisticians and somebody drawn to information mining in technological know-how or undefined. The book's assurance is wide, from supervised studying (prediction) to unsupervised studying. the numerous issues contain neural networks, help vector machines, type timber and boosting---the first accomplished remedy of this subject in any book.
This significant new version good points many themes now not coated within the unique, together with graphical versions, random forests, ensemble tools, least attitude regression & course algorithms for the lasso, non-negative matrix factorization, and spectral clustering. there's additionally a bankruptcy on tools for ``wide'' info (p larger than n), together with a number of trying out and fake discovery premiums.
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Extra resources for The Elements of Statistical Learning: Data Mining, Inference and Prediction (2nd Edition)
The Elements of Statistical Learning: Data Mining, Inference and Prediction (2nd Edition) by Trevor Hastie