C4.5: programs for machine learning
C4.5: programs for machine learning
An Evolutionary Algorithm for Integer Programming
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Automatic Feature Extraction for Classifying Audio Data
Machine Learning
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Selecting small audio feature sets in music classification by means of asymmetric mutation
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Multi-objective feature selection in music genre and style recognition tasks
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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Music classification is a complex problem which has gained high relevance for organizing large music collections. Different parameters concerning feature extraction, selection, processing and classification have a strong impact on the categorization quality. Since it is very difficult to design a deterministic approach which provides the efficient parameter tuning, we haven chosen a heuristic approach. In our work we apply and compare different evolution strategies for the optimization of feature selection and consolidation using three pre-defined personal user categories. Concepts of local search operators with domain-specific knowledge and self-adaptation are examined. Several suggestions based on an empirical study are discussed and ideas for future work are given.