Data mining and business analytics with R (Record no. 180099)

000 -LEADER
fixed length control field 02009 a2200193 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140323b2013 xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781118447147
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.74
Item number L3D2
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Ledolter, Johannes
9 (RLIN) 190651
245 ## - TITLE STATEMENT
Title Data mining and business analytics with R
Statement of responsibility, etc. Ledolter, Johannes
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Date of publication, distribution, etc. 2013
Name of publisher, distributor, etc. John Wiley & Sons
Place of publication, distribution, etc. New Jersey
300 ## - PHYSICAL DESCRIPTION
Extent xi, 351 p.
365 ## - TRADE PRICE
Price type code USD
Price amount 124.95
520 ## - SUMMARY, ETC.
Summary, etc. Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification.

Highlighting both underlying concepts and practical computational skills, Data Mining and Business Analytics with R begins with coverage of standard linear regression and the importance of parsimony in statistical modeling. The book includes important topics such as penalty-based variable selection (LASSO); logistic regression; regression and classification trees; clustering; principal components and partial least squares; and the analysis of text and network data. In addition, the book presents:

• A thorough discussion and extensive demonstration of the theory behind the most useful data mining tools

• Illustrations of how to use the outlined concepts in real-world situations

• Readily available additional data sets and related R code allowing readers to apply their own analyses to the discussed materials

• Numerous exercises to help readers with computing skills and deepen their understanding of the material

650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining
9 (RLIN) 56428
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element R (Computer program language)
9 (RLIN) 55638
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Commercial statistics
9 (RLIN) 11203
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Permanent Location Current Location Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Total Renewals Full call number Barcode Date last seen Date checked out Cost, replacement price Price effective from Koha item type
        Non-fiction Vikram Sarabhai Library Vikram Sarabhai Library General Stacks 2013-11-18 7 6497.40 5 13 005.74 L3D2 180282 2018-12-18 2018-10-03 8121.75 2013-11-14 Books

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