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R and Data Mining: Examples and Case Studies

R and Data Mining: Examples and Case Studies

R and Data Mining: Examples and Case Studies
Stock photo: cover may vary

R and Data Mining: Examples and Case Studies Hardback - 2013 - 1st Edition

by Zhao, Y

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  • Hardback

Description

Academic Press, 2013. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In poor condition, suitable as a reading copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780123969637
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Details

  • Title R and Data Mining: Examples and Case Studies
  • Author Zhao, Y
  • Binding Hardback
  • Edition number 1st
  • Edition 1
  • Pages 256
  • Volumes 1
  • Language ENG
  • Publisher Academic Press
  • Publication date 2013
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # 9868196
  • ISBN 9780123969637 / 0123969638
  • Weight 1.2 lbs (0.54 kg)
  • Dimensions 9 x 6.1 x 0.9 in (22.86 x 15.49 x 2.29 cm)
  • Themes
    • Aspects (Academic): Science/Technology Aspects
  • Category Mathematics
  • Library of Congress subjects Data mining, R (Computer program language)
  • Library of Congress Catalogue Number 2012044335
  • Dewey Decimal Code 006.312

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Reader reviews for R and Data Mining: Examples and Case Studies

From the publisher

R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis.
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