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Chapman and Hall/Crc Data Mining and Knowledge Discovery Ser.: Data Mining with R : Learning with Case Studies, Second Edition by Luis Torgo (2017, Hardcover)
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About this product
Product Identifiers
PublisherCRC Press LLC
ISBN-101482234890
ISBN-139781482234893
eBay Product ID (ePID)227666804
Product Key Features
Number of Pages426 Pages
LanguageEnglish
Publication NameData Mining with R : Learning with Case Studies, Second Edition
Publication Year2017
SubjectProgramming Languages / General, General, Databases / Data Mining, Statistics
TypeTextbook
Subject AreaComputers, Business & Economics
AuthorLuis Torgo
SeriesChapman and Hall/Crc Data Mining and Knowledge Discovery Ser.
FormatHardcover
Dimensions
Item Height0.7 in
Item Weight37.2 Oz
Item Length10.3 in
Item Width7.3 in
Additional Product Features
Edition Number2
Intended AudienceScholarly & Professional
LCCN2016-024995
Dewey Edition23
IllustratedYes
Dewey Decimal006.3/12
Table Of ContentIntroduction. I R AND DATA MINING. Introduction to R. Introduction to Data Mining. II CASE STUDIES. Predicting Algae Blooms. Predicting Stock Market Returns. Detecting Fraudulent Transactions. Classifying Microarray Samples
Edition DescriptionRevised edition,New Edition
SynopsisIf you want to learn how to analyze your data with R, this is your book. A broad range of real-world case studies highlights the breadth and depth of the R software. This expanded second edition delves deeper into topical explanations and updates and expands all case studies. 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., Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, including a new chapter that provides an introduction to data mining, to complement the already existing introduction to R. The second part includes case studies, and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R. The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies, and they are designed to be self-contained so the reader can start anywhere in the document. The book is accompanied by a set of freely available R source files that can be obtained at the book's web site. These files include all the code used in the case studies, and they facilitate the "do-it-yourself" approach followed in the book. Designed for users of data analysis tools, as well as researchers and developers, the book should be useful for anyone interested in entering the "world" of R and data mining. About the Author Luís Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. He teaches Data Mining in R in the NYU Stern School of Business' MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years, Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA., Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, including a new chapter that provides an introduction to data mining, to complement the already existing introduction to R. The second part includes case studies, and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R. The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies, and they are designed to be self-contained so the reader can start anywhere in the document. The book is accompanied by a set of freely available R source files that can be obtained at the book's web site. These files include all the code used in the case studies, and they facilitate the "do-it-yourself" approach followed in the book. Designed for users of data analysis tools, as well as researchers and developers, the book should be useful for anyone interested in entering the "world" of R and data mining. About the Author Lu s Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. Heteaches Data Mining in R in the NYU Stern School of Business' MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years, Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA.
LC Classification NumberQA76.9.D343T67 2017
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