A Feature-Based Serial Approach to Classifier Combination
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Abraham Kandel | Horst Bunke | Mark Last | Mark Last | H. Bunke | A. Kandel
[1] Fabio Roli,et al. A theoretical framework for dynamic classifier selection , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.
[2] Ching Y. Suen,et al. Combination of multiple classifier decisions for optical character recognition , 1997 .
[3] Lars Kai Hansen,et al. Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[4] Jon Atli Benediktsson,et al. Multiple Classifier Systems , 2015, Lecture Notes in Computer Science.
[5] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[6] Josef Kittler,et al. Multiple Classifier Systems: First International Workshop, MCS 2000 Cagliari, Italy, June 21-23, 2000 Proceedings , 2000 .
[7] Oded Maimon. Knowledge Discovery and Data Mining : The Info-Fuzzy Network (IFN) Methodology , 2000 .
[8] Hiroshi Motoda,et al. Feature Selection for Knowledge Discovery and Data Mining , 1998, The Springer International Series in Engineering and Computer Science.
[9] Jiri Matas,et al. On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[10] Catherine Blake,et al. UCI Repository of machine learning databases , 1998 .
[11] Hong Yan,et al. Prototype optimization for nearest neighbor classifiers using a two-layer perceptron , 1993, Pattern Recognit..
[12] G. Dunteman. Principal Components Analysis , 1989 .
[13] Josef Kittler,et al. Floating search methods in feature selection , 1994, Pattern Recognit. Lett..
[14] Fuad Rahman,et al. Serial Combination of Multiple Experts: A Unified Evaluation , 1999, Pattern Analysis & Applications.
[15] Tin Kam Ho,et al. The Random Subspace Method for Constructing Decision Forests , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[16] Leo Breiman,et al. Classification and Regression Trees , 1984 .
[17] Jae-On Kim,et al. Factor Analysis: Statistical Methods and Practical Issues , 1978 .
[18] Ron Kohavi,et al. Irrelevant Features and the Subset Selection Problem , 1994, ICML.
[19] Keki B. Irani,et al. Multi-interval discretization of continuos attributes as pre-processing for classi cation learning , 1993, IJCAI 1993.
[20] Fabio Roli,et al. Dynamic Classifier Selection , 2000, Multiple Classifier Systems.
[21] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[22] Aiko M. Hormann,et al. Programs for Machine Learning. Part I , 1962, Inf. Control..
[23] Essaid Bouktache,et al. A Fast Algorithm for the Nearest-Neighbor Classifier , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[24] Robert E. Schapire,et al. A Brief Introduction to Boosting , 1999, IJCAI.
[25] Abraham Kandel,et al. Information-theoretic algorithm for feature selection , 2001, Pattern Recognit. Lett..
[26] Andrew R. Webb,et al. Statistical Pattern Recognition , 1999 .
[27] Jürgen Schürmann,et al. Pattern classification , 2008 .
[28] W. Eric L. Grimson,et al. Constructing optimized prototypes for nearest neighbor classifiers , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.
[29] Jari Kangas. Comparison between two prototype representation schemes for a nearest neighbor classifier , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.
[30] John W. Tukey,et al. A Projection Pursuit Algorithm for Exploratory Data Analysis , 1974, IEEE Transactions on Computers.
[31] Robert P. W. Duin,et al. Experiments with Classifier Combining Rules , 2000, Multiple Classifier Systems.
[32] Larry A. Rendell,et al. The Feature Selection Problem: Traditional Methods and a New Algorithm , 1992, AAAI.
[33] Majid Ahmadi,et al. Pattern classification using an efficient KNNR , 1992, Pattern Recognit..
[34] Josef Kittler,et al. Multiple Classifier Systems , 2004, Lecture Notes in Computer Science.
[35] Horst Bunke,et al. Handbook of Character Recognition and Document Image Analysis , 1997 .
[36] James C. Bezdek,et al. Multiple-prototype classifier design , 1998, IEEE Trans. Syst. Man Cybern. Part C.
[37] Pavel Paclík,et al. Adaptive floating search methods in feature selection , 1999, Pattern Recognit. Lett..