ABSTRACT
Robust Methods for Data Reduction 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, dou
TABLE OF CONTENTS
part |2 pages
Part I Dimension Reduction
part |2 pages
Part II Sample Reduction