Empirical Study of Feature Selection Methods in Classification Export

@proceedings{azofra2008featureselection, abstract = {The use of feature selection can improve accuracy, efficiency, applicability and understandability of a learning process and the resulting learner. For this reason, many methods of automatic feature selection have been developed. By using the modularization of feature selection process, this paper evaluates a wide spectrum of these methods and some additional ones created by combination of different search and measure modules. The evaluation identifies the most interesting methods and shows some recommendations about which feature selection method should be used under different conditions.}, author = {Arauzo-Azofra, A. and Benitez, J. M.}, booktitle = {Hybrid Intelligent Systems, 2008. HIS '08. Eighth International Conference on}, citeulike-article-id = {4492994}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/HIS.2008.164}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4626693}, doi = {10.1109/HIS.2008.164}, journal = {Hybrid Intelligent Systems, 2008. HIS '08. Eighth International Conference on}, keywords = {featureselection}, pages = {584--589}, posted-at = {2009-05-08 13:22:21}, priority = {2}, title = {Empirical Study of Feature Selection Methods in Classification}, url = {http://dx.doi.org/10.1109/HIS.2008.164}, year = {2008} }

TY - CONF ID - azofra2008featureselection L3 - citeulike-article-id:4492994 N2 - The use of feature selection can improve accuracy, efficiency, applicability and understandability of a learning process and the resulting learner. For this reason, many methods of automatic feature selection have been developed. By using the modularization of feature selection process, this paper evaluates a wide spectrum of these methods and some additional ones created by combination of different search and measure modules. The evaluation identifies the most interesting methods and shows some recommendations about which feature selection method should be used under different conditions. JF - Hybrid Intelligent Systems, 2008. HIS '08. Eighth International Conference on EP - 589 TI - Empirical Study of Feature Selection Methods in Classification T2 - Hybrid Intelligent Systems, 2008. HIS '08. Eighth International Conference on SP - 584 KW - featureselection AU - Arauzo-Azofra, A AU - Benitez, JM PY - 2008/// UR - http://dx.doi.org/10.1109/HIS.2008.164 ER -