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978-3-540-48219-2

Multiple Classifier Systems

Publish Date: 2001

ISBN: 978-3-540-48219-2

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Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Support Vector Machine, have contributed to the development of - proved methods of pattern classi cation. However, while any performance gains are welcome, and often extremely signi cant from the practical point of view, it is increasingly more challenging to reach the point of perfection as de ned by the theoretical optimality of decision making in a given decision framework. The asymptoticity of gains that can be made for a single classi er is a re?- tion of the fact that any particular design, regardless of how good it is, simply provides just one estimate of the optimal decision rule.


Subject: Computer Science, Algorithmic Learning, Bagging, Boosting, Classification, Classifier Systems, Document Analysis, Image Analysis, Machine Learning, Multiple Classifier Systems, Neural Networks, Pattern Recognition, Remote Sensing, Time Series Analysis