Advances in neural information processing systems 2
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Second Order Derivatives for Network Pruning: Optimal Brain Surgeon
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Evaluating Feature Selection Methods for Learning in Data Mining Applications
HICSS '98 Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences-Volume 5 - Volume 5
The feature selection problem: traditional methods and a new algorithm
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
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This study discusses the problem of feature selection as one of the most fundamental problems in the field of the machine learning. Two novel approaches for feature selection in order to select a subset with relevant features are proposed. These approaches can be considered as a direct extension of the ensemble feature selection approach. The first one deals with identifying relevant features by using a single feature selection method. While, the second one uses different feature selection methods in order to identify more correctly the relevant features. An illustration shows the effectiveness of the proposed methods on artificial databases where we have a priori the informations about the relevant features.