Framework for efficient feature selection in genetic algorithm based data mining
暂无分享,去创建一个
[1] J.L. Castro,et al. A neuro-fuzzy approach for feature selection , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).
[2] Pier Luca Lanzi,et al. Fast feature selection with genetic algorithms: a filter approach , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).
[3] J. Elashoff,et al. On the choice of variables in classification problems with dichotomous variables. , 1967, Biometrika.
[4] Godfried T. Toussaint,et al. Note on optimal selection of independent binary-valued features for pattern recognition (Corresp.) , 1971, IEEE Trans. Inf. Theory.
[5] Josef Kittler,et al. Mathematics Methods of Feature Selection in Pattern Recognition , 1975, Int. J. Man Mach. Stud..
[6] J. K. Kinnear,et al. Advances in Genetic Programming , 1994 .
[7] Mohamed A. Deriche,et al. An optimal feature selection technique using the concept of mutual information , 2001, Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467).
[8] Saso Dzeroski,et al. Inductive Logic Programming and Knowledge Discovery in Databases , 1996, Advances in Knowledge Discovery and Data Mining.
[9] P. Nordin,et al. Explicitly defined introns and destructive crossover in genetic programming , 1996 .
[10] B. Chambless,et al. Information-theoretic feature selection for a neural behavioral model , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).
[11] Larry A. Rendell,et al. A Practical Approach to Feature Selection , 1992, ML.
[12] Roberto Battiti,et al. Using mutual information for selecting features in supervised neural net learning , 1994, IEEE Trans. Neural Networks.
[13] Jihoon Yang,et al. Feature Subset Selection Using a Genetic Algorithm , 1998, IEEE Intell. Syst..
[14] Michael J. Shaw,et al. A genetic algorithm-based approach to flexible flow-line scheduling with variable lot sizes , 1997, IEEE Trans. Syst. Man Cybern. Part B.
[15] Michael J. Shaw,et al. A Double-Layered Learning Approach to Acquiring Rules for Classification: Integrating Genetic Algorithms with Similarity-Based Learning , 1994, INFORMS J. Comput..
[16] Marimuthu Palaniswami,et al. Computational Intelligence: A Dynamic System Perspective , 1995 .
[17] Janet L. Kolodner,et al. Case-Based Reasoning , 1989, IJCAI 1989.
[18] Huan Liu,et al. Feature Selection via Discretization , 1997, IEEE Trans. Knowl. Data Eng..
[19] J. N. R. Jeffers,et al. Graphical Models in Applied Multivariate Statistics. , 1990 .
[20] C. Lee Giles,et al. Feature selection in Web applications by ROC inflections and powerset pruning , 2001, Proceedings 2001 Symposium on Applications and the Internet.
[21] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[22] Thomas M. Cover,et al. The Best Two Independent Measurements Are Not the Two Best , 1974, IEEE Trans. Syst. Man Cybern..
[23] Paul S. Bradley,et al. Feature Selection via Mathematical Programming , 1997, INFORMS J. Comput..
[24] Riyaz Sikora,et al. Learning control strategies for chemical processes: a distributed approach , 1992, IEEE Expert.
[25] Daryl Pregibon,et al. A Statistical Perspective on Knowledge Discovery in Databases , 1996, Advances in Knowledge Discovery and Data Mining.
[26] Tapio Elomaa,et al. A Geometric Approach to Feature Selection , 1994, ECML.
[27] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[28] Helmut Alt,et al. Approximate Matching of Polygonal Shapes (Extended Abstract) , 1991, SCG.