Feature Selection Inspired Classifier Ensemble Reduction
暂无分享,去创建一个
Fei Chao | Qiang Shen | Taoxin Peng | Ren Diao | Neal Snooke | Q. Shen | N. Snooke | R. Diao | Taoxin Peng | Fei Chao
[1] Jakub Wroblewski,et al. Ensembles of Classifiers Based on Approximate Reducts , 2001, Fundam. Informaticae.
[2] Loris Nanni,et al. Ensemblator: An ensemble of classifiers for reliable classification of biological data , 2007, Pattern Recognit. Lett..
[3] Chun-Nan Hsu,et al. The ANNIGMA-wrapper approach to fast feature selection for neural nets , 2002, IEEE Trans. Syst. Man Cybern. Part B.
[4] อนิรุธ สืบสิงห์,et al. Data Mining Practical Machine Learning Tools and Techniques , 2014 .
[5] Yoshua Bengio,et al. Série Scientifique Scientific Series No Unbiased Estimator of the Variance of K-fold Cross-validation No Unbiased Estimator of the Variance of K-fold Cross-validation , 2022 .
[6] Hiroshi Motoda,et al. Book Review: Computational Methods of Feature Selection , 2007, The IEEE intelligent informatics bulletin.
[7] Grigorios Tsoumakas,et al. Instance-Based Ensemble Pruning via Multi-Label Classification , 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.
[8] Witold Pedrycz,et al. A Tabu–Harmony Search-Based Approach to Fuzzy Linear Regression , 2011, IEEE Transactions on Fuzzy Systems.
[9] R. Boggia,et al. Genetic algorithms as a strategy for feature selection , 1992 .
[10] Carme Torras,et al. Assessing Image Features for Vision-Based Robot Positioning , 2001, J. Intell. Robotic Syst..
[11] Richard Jensen,et al. Measures for Unsupervised Fuzzy-Rough Feature Selection , 2009, ISDA.
[12] Qiang Shen,et al. Computational Intelligence and Feature Selection - Rough and Fuzzy Approaches , 2008, IEEE Press series on computational intelligence.
[13] Josef Kittler,et al. Multilabel classification using heterogeneous ensemble of multi-label classifiers , 2012, Pattern Recognit. Lett..
[14] Qiang Shen,et al. Facilitating efficient Mars terrain image classification with fuzzy-rough feature selection , 2011, Int. J. Hybrid Intell. Syst..
[15] Jonathan Lawry,et al. A linguistic decision tree approach to predicting storm surge , 2013, Fuzzy Sets Syst..
[16] K. Lee,et al. A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice , 2005 .
[17] James M. Keller,et al. A fuzzy K-nearest neighbor algorithm , 1985, IEEE Transactions on Systems, Man, and Cybernetics.
[18] Huan Liu,et al. Consistency-based search in feature selection , 2003, Artif. Intell..
[19] Fabio Roli,et al. An approach to the automatic design of multiple classifier systems , 2001, Pattern Recognit. Lett..
[20] Michael I. Jordan,et al. Feature selection for high-dimensional genomic microarray data , 2001, ICML.
[21] Hiroshi Motoda,et al. Computational Methods of Feature Selection , 2007 .
[22] Mark A. Hall,et al. Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning , 1999, ICML.
[23] L.E. Parker,et al. Design and performance improvements for fault detection in tightly-coupled multi-robot team tasks , 2008, IEEE SoutheastCon 2008.
[24] David W. Aha,et al. Instance-Based Learning Algorithms , 1991, Machine Learning.
[25] M. Mahdavi,et al. ARTICLE IN PRESS Available online at www.sciencedirect.com , 2007 .
[26] Ludmila I. Kuncheva,et al. Switching between selection and fusion in combining classifiers: an experiment , 2002, IEEE Trans. Syst. Man Cybern. Part B.
[27] Grigorios Tsoumakas,et al. Pruning an ensemble of classifiers via reinforcement learning , 2009, Neurocomputing.
[28] Morteza Haghir Chehreghani,et al. Novel meta-heuristic algorithms for clustering web documents , 2008, Appl. Math. Comput..
[29] Qiang Shen,et al. Feature Selection With Harmony Search , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[30] Ben J. A. Kröse,et al. A probabilistic model for appearance-based robot localization , 2001, Image and Vision Computing.
[31] Trevor Darrell,et al. Multi-View Learning in the Presence of View Disagreement , 2008, UAI 2008.
[32] Richard Jensen,et al. Measures for Unsupervised Fuzzy-Rough Feature Selection , 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.
[33] Manuela M. Veloso,et al. Feature selection for activity recognition in multi-robot domains , 2008, AAAI 2008.
[34] A. Marín-Hernández,et al. Significant Feature Selection in Range Scan Data for Geometrical Mobile Robot Mapping , 2006 .
[35] Mario Marchand,et al. Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[36] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[37] Andrzej Skowron,et al. Rough set methods in feature selection and recognition , 2003, Pattern Recognit. Lett..
[38] John Q. Gan,et al. Constructing accurate and parsimonious fuzzy models with distinguishable fuzzy sets based on an entropy measure , 2006, Fuzzy Sets Syst..
[39] Mykola Pechenizkiy,et al. Diversity in search strategies for ensemble feature selection , 2005, Inf. Fusion.
[40] Qiang Shen,et al. A Distance Measure Approach to Exploring the Rough Set Boundary Region for Attribute Reduction , 2010, IEEE Transactions on Knowledge and Data Engineering.
[41] Bernard Zenko,et al. Is Combining Classifiers Better than Selecting the Best One , 2002, ICML.
[42] Qiang Shen,et al. Fuzzy-rough classifier ensemble selection , 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).
[43] Rajen B. Bhatt,et al. On fuzzy-rough sets approach to feature selection , 2005, Pattern Recognit. Lett..
[44] John Q. Gan,et al. Constructing L2-SVM-Based Fuzzy Classifiers in High-Dimensional Space With Automatic Model Selection and Fuzzy Rule Ranking , 2007, IEEE Transactions on Fuzzy Systems.
[45] Zong Woo Geem,et al. Recent Advances In Harmony Search Algorithm , 2010, Recent Advances In Harmony Search Algorithm.
[46] Changjing Shang,et al. Fuzzy-rough feature selection aided support vector machines for Mars image classification , 2013, Comput. Vis. Image Underst..
[47] Zexuan Zhu,et al. Wrapper–Filter Feature Selection Algorithm Using a Memetic Framework , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[48] Robert A. Jacobs,et al. Methods For Combining Experts' Probability Assessments , 1995, Neural Computation.
[49] Justin C. W. Debuse,et al. Feature Subset Selection within a Simulated Annealing Data Mining Algorithm , 1997, Journal of Intelligent Information Systems.
[50] M. Raju,et al. Optimal Network Reconfiguration of Large-Scale Distribution System Using Harmony Search Algorithm , 2011, IEEE Transactions on Power Systems.
[51] Pat Langley,et al. Estimating Continuous Distributions in Bayesian Classifiers , 1995, UAI.
[52] Huan Liu,et al. Feature Selection for Classification , 1997, Intell. Data Anal..
[53] Sean R Eddy,et al. What is dynamic programming? , 2004, Nature Biotechnology.
[54] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[55] Qiang Shen,et al. New Approaches to Fuzzy-Rough Feature Selection , 2009, IEEE Transactions on Fuzzy Systems.
[56] Bernard Zenko,et al. Is Combining Classifiers with Stacking Better than Selecting the Best One? , 2004, Machine Learning.
[57] João Paulo Papa,et al. A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection , 2011, Comput. Electr. Eng..
[58] Xiangyang Wang,et al. Feature selection based on rough sets and particle swarm optimization , 2007, Pattern Recognit. Lett..
[59] Ron Kohavi,et al. Wrappers for Feature Subset Selection , 1997, Artif. Intell..
[60] Tin Kam Ho,et al. The Random Subspace Method for Constructing Decision Forests , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[61] Chris Cornelis,et al. Fuzzy-Rough Nearest Neighbour Classification , 2011, Trans. Rough Sets.