By Stéphane Tufféry
This e-book seems at either classical and up to date innovations of knowledge mining, resembling clustering, discriminant research, logistic regression, generalized linear types, regularized regression, PLS regression, choice timber, neural networks, help vector machines, Vapnik thought, naive Bayesian classifier, ensemble studying and detection of organization ideas. they're mentioned in addition to illustrative examples in the course of the publication to give an explanation for the speculation of those equipment, in addition to their strengths and limitations.
Presents a complete creation to all strategies utilized in facts mining and statistical studying, from classical to most recent techniques.
Starts from easy rules as much as complicated concepts.
Includes many step by step examples with the most software program (R, SAS, IBM SPSS) in addition to an intensive dialogue and comparability of these software.
Gives functional information for facts mining implementation to resolve genuine global problems.
Looks at a variety of instruments and functions, similar to organization principles, internet mining and textual content mining, with a unique specialize in credits scoring.
Supported via an accompanying web hosting datasets and consumer analysis.
Statisticians and enterprise intelligence analysts, scholars in addition to laptop technological know-how, biology, advertising and fiscal probability pros in either advertisement and govt enterprises throughout all enterprise and sectors will take advantage of this book.
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Extra info for Data Mining and Statistics for Decision Making (Wiley Series in Computational Statistics)