Eigenclassifiers for combining correlated classifiers
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[1] Ethem Alpaydin,et al. Incremental construction of classifier and discriminant ensembles , 2009, Inf. Sci..
[2] Christino Tamon,et al. On the Boosting Pruning Problem , 2000, ECML.
[3] Arun Ross,et al. Score normalization in multimodal biometric systems , 2005, Pattern Recognit..
[4] I. Jolliffe. Discarding Variables in a Principal Component Analysis. Ii: Real Data , 1973 .
[5] B. C. Brookes,et al. Information Sciences , 2020, Cognitive Skills You Need for the 21st Century.
[6] Stephen D. Bay. Combining Nearest Neighbor Classifiers Through Multiple Feature Subsets , 1998, ICML.
[7] A. C. Rencher. Interpretation of Canonical Discriminant Functions, Canonical Variates, and Principal Components , 1992 .
[8] Cigdem Demir,et al. Cost-conscious classifier ensembles , 2005, Pattern Recognit. Lett..
[9] Ludmila I. Kuncheva,et al. Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy , 2003, Machine Learning.
[10] Fabio Roli,et al. A theoretical and experimental analysis of linear combiners for multiple classifier systems , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[12] Noel E. Sharkey,et al. The "Test and Select" Approach to Ensemble Combination , 2000, Multiple Classifier Systems.
[13] Ethem Alpaydın,et al. Combined 5 x 2 cv F Test for Comparing Supervised Classification Learning Algorithms , 1999, Neural Comput..
[14] Bogdan Gabrys,et al. Classifier selection for majority voting , 2005, Inf. Fusion.
[15] William Nick Street,et al. Ensemble Pruning Via Semi-definite Programming , 2006, J. Mach. Learn. Res..
[16] P. N. Suganthan,et al. Ensemble of niching algorithms , 2010, Inf. Sci..
[17] Michael J. Pazzani,et al. A Principal Components Approach to Combining Regression Estimates , 1999, Machine Learning.
[18] Ethem Alpaydin,et al. Linear Discriminant Trees , 2000, ICML.
[19] Ludmila I. Kuncheva,et al. Combining Pattern Classifiers: Methods and Algorithms , 2004 .
[20] Xi-Zhao Wang,et al. Improving Generalization of Fuzzy IF--THEN Rules by Maximizing Fuzzy Entropy , 2009, IEEE Transactions on Fuzzy Systems.
[21] Ian H. Witten,et al. Issues in Stacked Generalization , 2011, J. Artif. Intell. Res..
[22] Xin Yao,et al. Diversity creation methods: a survey and categorisation , 2004, Inf. Fusion.
[23] Ethem Alpaydin,et al. Combining multiple representations and classifiers for pen-based handwritten digit recognition , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.
[24] Yoav Freund,et al. Experiments with a New Boosting Algorithm , 1996, ICML.
[25] William B. Yates,et al. Engineering Multiversion Neural-Net Systems , 1996, Neural Computation.
[26] Christopher J. Merz,et al. Using Correspondence Analysis to Combine Classifiers , 1999, Machine Learning.
[27] Rich Caruana,et al. Ensemble selection from libraries of models , 2004, ICML.
[28] Subhash C. Bagui,et al. Combining Pattern Classifiers: Methods and Algorithms , 2005, Technometrics.
[29] Xiaoyi Jiang,et al. A dynamic classifier ensemble selection approach for noise data , 2010, Inf. Sci..
[30] David H. Wolpert,et al. Stacked generalization , 1992, Neural Networks.
[31] Rui Xia,et al. Ensemble of feature sets and classification algorithms for sentiment classification , 2011, Inf. Sci..
[32] Fabio Roli,et al. Methods for Designing Multiple Classifier Systems , 2001, Multiple Classifier Systems.
[33] Francisco Herrera,et al. Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power , 2010, Inf. Sci..
[34] Janez Demsar,et al. Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..
[35] Cheng-Lin Liu,et al. Classifier combination based on confidence transformation , 2005, Pattern Recognit..
[36] Ethem Alpaydin,et al. Voting over Multiple Condensed Nearest Neighbors , 1997, Artificial Intelligence Review.
[37] Thomas G. Dietterich,et al. Pruning Adaptive Boosting , 1997, ICML.
[38] Li-Juan Wang,et al. An improved multiple fuzzy NNC system based on mutual information and fuzzy integral , 2011, Int. J. Mach. Learn. Cybern..
[39] Tin Kam Ho,et al. The Random Subspace Method for Constructing Decision Forests , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[40] Sarunas Raudys,et al. Trainable fusion rules. I. Large sample size case , 2006, Neural Networks.
[41] Geoffrey I. Webb,et al. To Select or To Weigh: A Comparative Study of Linear Combination Schemes for SuperParent-One-Dependence Estimators , 2007, IEEE Transactions on Knowledge and Data Engineering.
[42] Xizhao Wang,et al. Induction of multiple fuzzy decision trees based on rough set technique , 2008, Inf. Sci..
[43] Wei Tang,et al. Ensembling neural networks: Many could be better than all , 2002, Artif. Intell..
[44] J. Neyman,et al. Interpretation of Canonical Discriminant Functions, Canonical Variates, and Principal Components , 1992 .
[45] Ludmila I. Kuncheva. Diversity in multiple classifier systems , 2005, Inf. Fusion.
[46] L. Kuncheva,et al. Combining classifiers: Soft computing solutions. , 2001 .
[47] Ponnuthurai N. Suganthan,et al. Ensemble strategies with adaptive evolutionary programming , 2010, Inf. Sci..
[48] Sankar K. Pal,et al. Pattern Recognition: From Classical to Modern Approaches , 2001 .
[49] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[50] Mehmet Aydin Ula. INCREMENTAL CONSTRUCTION OF COST-CONSCIOUS ENSEMBLES USING MULTIPLE LEARNERS AND REPRESENTATIONS IN MACHINE LEARNING , 2009 .
[51] Kagan Tumer,et al. Error Correlation and Error Reduction in Ensemble Classifiers , 1996, Connect. Sci..
[52] Dong Ling Tong,et al. Genetic Algorithm-Neural Network (GANN): a study of neural network activation functions and depth of genetic algorithm search applied to feature selection , 2010, Int. J. Mach. Learn. Cybern..
[53] Robert A. Jacobs,et al. Bias/Variance Analyses of Mixtures-of-Experts Architectures , 1997, Neural Computation.
[54] Robert P. W. Duin,et al. Is independence good for combining classifiers? , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.
[55] Fabio Roli,et al. Multiple classifier systems for robust classifier design in adversarial environments , 2010, Int. J. Mach. Learn. Cybern..