Artificial Intelligence and Information Technology Evaluating feature selection methods for learning in data mining applications
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[1] Thomas M. Cover,et al. The Best Two Independent Measurements Are Not the Two Best , 1974, IEEE Trans. Syst. Man Cybern..
[2] Thomas G. Dietterich,et al. Learning with Many Irrelevant Features , 1991, AAAI.
[3] Ron Kohavi,et al. Wrappers for performance enhancement and oblivious decision graphs , 1995 .
[4] Josef Kittler,et al. Pattern recognition : a statistical approach , 1982 .
[5] Thomas G. Dietterich,et al. Learning Boolean Concepts in the Presence of Many Irrelevant Features , 1994, Artif. Intell..
[6] Edward Wilson Reed,et al. Commercial Bank Management , 1963 .
[7] Keinosuke Fukunaga,et al. Introduction to Statistical Pattern Recognition , 1972 .
[8] A. Abdel-khalik,et al. Information Choice and Utilization in an Experiment on Default Prediction , 1980 .
[9] Godfried T. Toussaint,et al. Note on optimal selection of independent binary-valued features for pattern recognition (Corresp.) , 1971, IEEE Trans. Inf. Theory.
[10] Selwyn Piramuthu,et al. Improving Connectionist Learning with Symbolic Feature Construction , 1992 .
[11] L. Milne. Feature Selection Using Neural Networks with Contribution Measures , 1995 .
[12] J. Ross Quinlan,et al. Decision trees and decision-making , 1990, IEEE Trans. Syst. Man Cybern..
[13] William S. Meisel,et al. Computer-oriented approaches to pattern recognition , 1972 .
[14] Ron Kohavi,et al. Irrelevant Features and the Subset Selection Problem , 1994, ICML.
[15] Larry A. Rendell,et al. A Practical Approach to Feature Selection , 1992, ML.
[16] Melody Y. Kiang,et al. Managerial Applications of Neural Networks: The Case of Bank Failure Predictions , 1992 .
[17] Roberto Battiti,et al. Using mutual information for selecting features in supervised neural net learning , 1994, IEEE Trans. Neural Networks.
[18] C. Chang. Dynamic programming as applied to feature subset selection in a pattern recognition system , 1972, ACM Annual Conference.
[19] Daphne Koller,et al. Toward Optimal Feature Selection , 1996, ICML.
[20] Steve Jameson,et al. Information Discovery in High-Volume, Frequently Changing Data , 1995, IEEE Expert.
[21] J. Elashoff,et al. On the choice of variables in classification problems with dichotomous variables. , 1967, Biometrika.
[22] Josef Kittler,et al. Mathematics Methods of Feature Selection in Pattern Recognition , 1975, Int. J. Man Mach. Stud..
[23] Hiroshi Motoda,et al. Feature Extraction, Construction and Selection: A Data Mining Perspective , 1998 .
[24] Jihoon Yang,et al. Feature Subset Selection Using a Genetic Algorithm , 1998, IEEE Intell. Syst..
[25] Jack Sklansky,et al. A note on genetic algorithms for large-scale feature selection , 1989, Pattern Recognit. Lett..
[26] J. Ross Quinlan,et al. Simplifying Decision Trees , 1987, Int. J. Man Mach. Stud..
[27] Josef Kittler,et al. Floating search methods for feature selection with nonmonotonic criterion functions , 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).
[28] Josef Kittler,et al. Divergence Based Feature Selection for Multimodal Class Densities , 1996, IEEE Trans. Pattern Anal. Mach. Intell..
[29] Tim Watson,et al. Problems with Using Genetic Algorithms for Neural Network Feature Selection , 1994, ECAI.
[30] Igor Kononenko,et al. Estimating Attributes: Analysis and Extensions of RELIEF , 1994, ECML.
[31] Huan Liu,et al. Neural-network feature selector , 1997, IEEE Trans. Neural Networks.
[32] Tapio Elomaa,et al. A Geometric Approach to Feature Selection , 1994, ECML.
[33] Sholom M. Weiss,et al. Feature Extraction for Massive Data Mining , 1995, KDD.
[34] Hiroshi Motoda,et al. Feature Selection for Knowledge Discovery and Data Mining , 1998, The Springer International Series in Engineering and Computer Science.
[35] Ron Kohavi,et al. Useful Feature Subsets and Rough Set Reducts , 1994 .
[36] Heidar A. Malki,et al. Using the Karhunen-Loe've transformation in the back-propagation training algorithm , 1991, IEEE Trans. Neural Networks.
[37] Maciej Modrzejewski,et al. Feature Selection Using Rough Sets Theory , 1993, ECML.