Guyon I. et al. Feature Extraction. Foundations and Applications

The present book is organized around the results of a benchmark that took place in 2003. Dozens of research groups competed on five large feature selection problems from various application domains: medical diagnosis, text processing, drug discovery, and handwriting recognition. The results of this
effort pave the way to a new generation of methods capable of analyzing data tables with million of lines and/or columns.
Part II of the book summarizes the results of the competition and gathers the papers describing the methods used by the top ranking participants. Following the competition, a NIPS workshop took place in December 2003 to discuss the outcomes of the competition and new avenues in feature extraction.
The contributions providing new perspectives are found in Part III of the book. Part I provides all the necessary foundations to understand the recent advances made in Parts II and III. The book is complemented by appendices and by a web site. The appendices include fact sheets summarizing the methods used in the competition, tables of results of the competition, and a summary of basic concepts of statistics.
This book is directed to students, researchers, and engineers. It presents recent advances in the field and complements an earlier book (Liu and Motoda, 1998), which provides a thorough bibliography and presents methods of historical interest, but explores only small datasets and ends before the new era of kernel methods. Readers interested in the historical aspects of the problem are also directed to (Devijver and Kittler, 1982). A completely novice reader will find all the necessary elements to understand the material of the book presented in the tutorial chapters of Part I. The book can be used as teaching material for a graduate class in statistics and machine learning, Part I supporting the lectures, Part II and III providing readings, and the CD providing data for computer projects.