Donald C. Wunsch

Alexander N. Gorban

Andrei Zinovyev

Balázs Kégl

In 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a prototype for many other tools of data analysis, visualization and dimension reduction: Independent Component Analysis (ICA), Multidimensional Scaling (MDS), Nonlinear PCA (NLPCA), Self Organizing Maps (SOM), etc. The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering algorithms, principal manifolds and SOM. New approaches to NLPCA, principal manifolds, branching principal components and topology preserving mappings are described as well. Presentation of algorithms is supplemented by case studies, from engineering to astronomy, but mostly of biological data: analysis of microarray and metabolite data. The volume ends with a tutorial "PCA and K-means decipher genome". The book is meant to be useful for practitioners in applied data analysis in life sciences, engineering, physics and chemistry; it will also be valuable to PhD students and researchers in computer sciences, applied mathematics and statistics.

Principal Manifolds for Data Visualization and Dimension Reduction

Guy Lapalme

Canadian Society for Computational Studies of Intelligence. Conference

Canadian Society for Computational Studies of Intelligence

This book constitutes the refereed proceedings of the 18th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2005, held in Victoria, Canada in May 2005. The revised full papers and 19 revised short papers presented were carefully reviewed and selected from 135 submission. The papers are organized in topical sections on agents, constraint satisfaction and search, data mining, knowledge representation and reasoning, machine learning, natural language processing, and reinforcement learning.

18th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2005, Victoria, Canada, May 9-11, 2005, Proceedings

Advances in Artificial Intelligence

Balázs Kégl

Books

Your next favorite book is out there