Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
High-performing feature selection for text classification
Proceedings of the eleventh international conference on Information and knowledge management
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
An analysis of the coupling between training set and neighborhood sizes for the kNN classifier
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Combination of feature selection methods for text categorisation
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Evaluation of feature combination approaches for text categorisation
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Comparison of text feature selection policies and using an adaptive framework
Expert Systems with Applications: An International Journal
Identification of micro RNA biomarkers for cancer by combining multiple feature selection techniques
Journal of Computational Methods in Sciences and Engineering
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We introduce several methods of combining feature selectors for text classification. Results from a large investigation of these combinations are summarized. Easily constructed combinations of feature selectors are shown to improve peak R-precision and F1 at statistically significant levels.