Data mining with R: learning with case studies (Record no. 201588)

000 -LEADER
fixed length control field 02981 a2200193 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151208b2011 xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781439810187
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Item number T6D2
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Torgo, Luis
9 (RLIN) 325031
245 ## - TITLE STATEMENT
Title Data mining with R: learning with case studies
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Boca Raton
Name of publisher, distributor, etc CRC Press
Date of publication, distribution, etc 2011
300 ## - PHYSICAL DESCRIPTION
Extent xv, 289 p.
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Chapman & Hall/CRC data mining and knowledge discovery series
9 (RLIN) 324931
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Table of Contents:<br/><br/>1. Introduction<br/>1.1. How to Read This Book<br/>1.2. A Short Introduction to R<br/>1.3. A Short Introduction to MySQL<br/><br/>2. Predicting Algae Blooms<br/>2.1. Problem Description and Objectives<br/>2.2. Data Description<br/>2.3. Loading the Data into R<br/>2.4. Data Visualization and Summarization<br/>2.5. Unknown Values<br/>2.6. Obtaining Prediction Models<br/>2.7. Model Evaluation and Selection<br/>2.8. Predictions for the 7 Algae <br/><br/>3. Predicting Stock Market Returns<br/>3.1. Problem Description and Objectives<br/>3.2. The Available Data<br/>3.3. Defining the Prediction Tasks<br/>3.4. The Prediction Models<br/>3.5. From Predictions into Actions<br/>3.6. Model Evaluation and Selection<br/>3.7. The Trading System<br/><br/>4. Detecting Fraudulent Transactions<br/>4.1. Problem Description and Objectives<br/>4.2. The Available Data<br/>4.3. Defining the Data Mining Tasks<br/>4.4. Obtaining Outlier Rankings<br/><br/>5. Classifying Microarray Samples<br/>5.1. Problem Description and Objectives<br/>5.2. The Available Data<br/>5.3. Gene (Feature) Selection<br/>5.4. Predicting Cytogenetic Abnormalities<br/>
520 ## - SUMMARY, ETC.
Summary, etc 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.<br/><br/>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:<br/><br/> Predicting algae blooms<br/> Predicting stock market returns<br/> Detecting fraudulent transactions<br/> Classifying microarray samples<br/><br/>With these case studies, the author supplies all necessary steps, code, and data.<br/> <br/>Web Resource<br/>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.<br/><br/>(https://www.crcpress.com/Data-Mining-with-R-Learning-with-Case-Studies/Torgo/9781439810187)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining - Case studies
9 (RLIN) 324932
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element R (Computer program language)
9 (RLIN) 324933
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Permanent location Current location Shelving location Date acquired Source of acquisition Cost, normal purchase price Item location Total Checkouts Total Renewals Full call number Barcode Date last seen Date last borrowed Cost, replacement price Koha item type
          Non-fiction Vikram Sarabhai Library Vikram Sarabhai Library   10/12/2015 Natraj Book Centre 4940.75 Slot 105 (0 Floor, West Wing) 4 6 006.312 T6D2 190598 07/09/2018 22/03/2018 6175.94 Books

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