{
"item_title" : "Robust Methods for Data Reduction",
"item_author" : [" Alessio Farcomeni", "Luca Greco "],
"item_description" : "This book gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis. Using real examples, the authors show how to implement the procedures in R. The code and data for the examples are available on the book's CRC Press web page. ",
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Overview
This book gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis. Using real examples, the authors show how to implement the procedures in R. The code and data for the examples are available on the book's CRC Press web page.
This item is Non-Returnable
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Details
- ISBN-13: 9781466590625
- ISBN-10: 1466590629
- Publisher: CRC Press
- Publish Date: April 2015
- Dimensions: 9.2 x 6.3 x 0.9 inches
- Shipping Weight: 1.25 pounds
- Page Count: 298
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