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020    9781439810187|qhardback 
020    1439810184|qhardback 
035    (OCoLC)ocn665064348 
035    (OCoLC)665064348 
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050 00 QA76.9.D343|bT67 2011 
082 00 006.3/12|222 
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090    QA76.9.D343 T67 2011 
100 1  Torgo, Luís.|0https://id.loc.gov/authorities/names/
       n2010062357 
245 10 Data mining with R :|blearning with case studies /|cLuís 
       Torgo. 
264  1 Boca Raton :|bChapman & Hall/CRC,|c[2011] 
264  4 |c©2011 
300    xv, 289 pages :|billustrations ;|c25 cm. 
336    text|btxt|2rdacontent 
337    unmediated|bn|2rdamedia 
338    volume|bnc|2rdacarrier 
490 1  Chapman & Hall/CRC data mining and knowledge discovery 
       series 
504    Includes bibliographical references (pages 269-277) and 
       indexes. 
520    "The versatile capabilities and large set of add-on 
       packages make R an excellent alternative to many existing 
       and often expensive data mining tools. Exploring this area
       from the perspective of a practitioner, Data mining with R
       : learning with case studies uses practical examples to 
       illustrate the power of R and data mining. Assuming no 
       prior knowledge of R or data mining/statistical techniques,
       the book covers a diverse set of problems that pose 
       different challenges in terms of size, type of data, goals
       of analysis, and analytical tools. To present the main 
       data mining processes and techniques, the author takes a 
       hands-on approach that utilizes a series of detailed, real
       -world case studies: predicting algae blooms, predicting 
       stock market returns, detecting fraudulent transactions, 
       classifying microarray samples. With these case studies, 
       the author supplies all necessary steps, code, and data. 
       Resource: A supporting website mirrors the do-it-yourself 
       approach of the text. It offers a collection of freely 
       available R source files that encompass all the code used 
       in the case studies. The site also provides the data sets 
       from the case studies as well as an R package of several 
       functions"--|cProvided by publisher. 
520    "This hands-on book uses practical examples to illustrate 
       the power of R and data mining. Assuming no prior 
       knowledge of R or data mining/statistical techniques, it 
       covers a diverse set of problems that pose different 
       challenges in terms of size, type of data, goals of 
       analysis, and analytical tools. The main data mining 
       processes and techniques are presented through detailed, 
       real-world case studies. With these case studies, the 
       author supplies all necessary steps, code, and data. 
       Mirroring the do-it-yourself approach of the text, the 
       supporting website provides data sets and R code"--
       |cProvided by publisher. 
650  0 Data mining|0https://id.loc.gov/authorities/subjects/
       sh97002073|vCase studies.|0https://id.loc.gov/authorities/
       subjects/sh99001484 
650  0 R (Computer program language)|0https://id.loc.gov/
       authorities/subjects/sh2002004407 
650  7 Data mining.|2fast|0https://id.worldcat.org/fast/887946 
650  7 R (Computer program language)|2fast|0https://
       id.worldcat.org/fast/1086207 
655  7 Case studies.|2fast|0https://id.worldcat.org/fast/1423765 
655  7 Case studies.|2lcgft|0https://id.loc.gov/authorities/
       genreForms/gf2017026140 
830  0 Chapman & Hall/CRC data mining and knowledge discovery 
       series.|0https://id.loc.gov/authorities/names/no2007060486
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