Data Analysis

This book is organized around two complementary families of methods for data analysis. Its first part is devoted to methods that seek relevant dimensions of data, where the variables obtained provide a synthetic description that often results in a graphical representation of the data; this follows a general presentation of discriminating analysis. The emphasis is on reducing data to meaningful dimensions that can be visualized and interpreted.

The second part is devoted to clustering methods, which constitute another approach that is often complementary to the dimension-finding methods of the first part, used to synthesize and analyze the data. The book concludes by examining the links existing between data mining and data analysis. This structure situates classical data analysis alongside the emerging concerns of data mining.