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Data mining with R = learning with c...
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Torgo, Luís.
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Data mining with R = learning with case studies /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Data mining with R/ Luís Torgo.
其他題名:
learning with case studies /
作者:
Torgo, Luís.
出版者:
Boca Raton, FL :Chapman & Hall/CRC, : c2011.,
面頁冊數:
1 online resource (xv, 289 p.) :ill.
標題:
Data mining -
電子資源:
http://www.crcnetbase.com/isbn/9781439810187
ISBN:
9781439876404 (electronic bk.)
Data mining with R = learning with case studies /
Torgo, Luís.
Data mining with R
learning with case studies /[electronic resource] :Luís Torgo. - Boca Raton, FL :Chapman & Hall/CRC,c2011. - 1 online resource (xv, 289 p.) :ill. - Chapman & Hall/CRC data mining and knowledge discovery series. - Chapman & Hall/CRC data mining and knowledge discovery series..
Includes bibliographical references and indexes.
"The versatile capabilities and large set of addon 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 handson approach that utilizes a series of detailed, realworld 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 doit-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"--
ISBN: 9781439876404 (electronic bk.)Subjects--Topical Terms:
744342
Data mining
Index Terms--Genre/Form:
542853
Electronic books.
LC Class. No.: QA76.9.D343 / T67 2011
Dewey Class. No.: 006.3/12
Data mining with R = learning with case studies /
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"The versatile capabilities and large set of addon 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 handson approach that utilizes a series of detailed, realworld 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 doit-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"--
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"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"--
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http://www.crcnetbase.com/isbn/9781439810187
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