By Stéphane Tufféry
This booklet seems to be at either classical and up to date suggestions of information mining, resembling clustering, discriminant research, logistic regression, generalized linear versions, regularized regression, PLS regression, selection bushes, neural networks, help vector machines, Vapnik concept, naive Bayesian classifier, ensemble studying and detection of organization ideas. they're mentioned in addition to illustrative examples during the publication to provide an explanation for the speculation of those equipment, in addition to their strengths and limitations.
Key Features:
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Presents a entire advent to all concepts utilized in information mining and statistical studying, from classical to most recent techniques.
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Starts from uncomplicated rules as much as complicated concepts.
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Includes many step by step examples with the most software program (R, SAS, IBM SPSS) in addition to a radical dialogue and comparability of these software.
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Gives useful information for info mining implementation to unravel genuine global problems.
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Looks at quite a number instruments and functions, akin to organization ideas, net mining and textual content mining, with a unique concentrate on credits scoring.
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Supported by way of an accompanying internet hosting datasets and consumer analysis.
Statisticians and company intelligence analysts, scholars in addition to desktop technology, biology, advertising and monetary chance execs in either advertisement and govt organisations throughout all enterprise and sectors will take advantage of this book.
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Data Mining and Statistics for Decision Making (Wiley Series in Computational Statistics)
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