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Three Hours on Multiple Classififier Systems

Three Hours on Multiple Classififier Systems

This video was recorded at The Analysis of Patterns, Cagliari 2009. Motivations and basic concepts Motivations of multiple classifier systems. The "worst" case and "best" case motivations. Practical and theoretical motivations. Basic concepts. Architectures for multiple classifier systems. Ensemble types, combiner types. The concept of classifier "diversity". The design cycle of a multiple classifier system. Creating multiple classifiers Systematic methods for creating classifier ensembles. Methods based on training data manipulation: data splitting methods, Bagging and Boosting. Methods based on input and output feature manipulation: feature selection, the Random Subspace method, noise injection, and error-correcting codes. Combining multiple classifiers Methods for combining multiple... Show More


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