PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

An introduction to feature extraction
Isabelle Guyon and Andre Elisseeff
In: Feature Extraction: Foundations and Applications Studies in Fuzziness and Soft Computing . (2006) Springer Verlag , Germany , pp. 1-25. ISBN 3540354875


Feature extraction addresses the problem of finding the most compact and informative set of features, to improve the efficiency or data storage and processing. Defining feature vectors remains the most common and convenient means of data representation for classification and regression problems. Data can then be stored in simple tables (lines representing ``entries", ``data points, ``samples", or ``patterns", and columns representing ``features"). Each feature results from a quantitative or qualitative measurement, it is an ``attribute" or a ``variable". Modern feature extraction methodology is driven by the size of the data tables, which is ever increasing as data storage becomes more and more efficient. After many years of parallel efforts, researchers in Soft-Computing, Statistics, Machine Learning, and Knowledge Discovery, who are interested in predictive modeling are uniting their effort to advance the problem of feature extraction. The recent advances made in both sensor technologies and machine learning techniques make it possible to design recognition systems, which are capable of performing tasks that could not be performed in the past. Feature extraction lies at the center of these advances with applications in the pharmaco-medical industry, oil industry, industrial inspection and diagnosis systems, speech recognition, biotechnology, Internet, targeted marketing and many of other emerging applications. This chapter introduces the book "Feature Extraction: Foundations and Applications", organized around the results of a benchmark that took place in 2003 (the website of the challenge is still active) and whose results were discussed at the NIPS 2003 workshop on feature extraction. This book is a step towards validating, unifying, and formalizing approaches. The introduction chapter presents an overview of the field of feature extraction, the results presented in the book, and a research outlook.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:2475
Deposited By:Isabelle Guyon
Deposited On:22 November 2006