Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Neural networks and the bias/variance dilemma
Neural Computation
C4.5: programs for machine learning
C4.5: programs for machine learning
Learning Boolean concepts in the presence of many irrelevant features
Artificial Intelligence
Journal of the ACM (JACM)
On the practical applicability of VC dimension bounds
Neural Computation
Machine Learning
On the Accuracy of Meta-learning for Scalable Data Mining
Journal of Intelligent Information Systems
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature selection for ensembles
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Efficient GA Based Techniques for Classification
Applied Intelligence
A Survey of Methods for Scaling Up Inductive Algorithms
Data Mining and Knowledge Discovery
Combining Multiple K-Nearest Neighbor Classifiers for Text Classification by Reducts
DS '02 Proceedings of the 5th International Conference on Discovery Science
Generalization Bounds for Decision Trees
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
Ensemble Feature election with the Simple Bayesian Classification in Medical Diagnostics
CBMS '02 Proceedings of the 15th IEEE Symposium on Computer-Based Medical Systems (CBMS'02)
A Compact and Accurate Model for Classification
IEEE Transactions on Knowledge and Data Engineering
Learning Ensembles from Bites: A Scalable and Accurate Approach
The Journal of Machine Learning Research
Information Sciences: an International Journal - Special issue: Soft computing data mining
Multiknowledge for decision making
Knowledge and Information Systems
Decomposition methodology for classification tasks: a meta decomposer framework
Pattern Analysis & Applications
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Feature set decomposition for decision trees
Intelligent Data Analysis
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Induction of selective Bayesian classifiers
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Constructing rough decision forests
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Nonparametric multivariate density estimation: a comparative study
IEEE Transactions on Signal Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Subspace based feature selection for pattern recognition
Information Sciences: an International Journal
Privacy-preserving data mining: A feature set partitioning approach
Information Sciences: an International Journal
Exploiting label dependencies for improved sample complexity
Machine Learning
Hi-index | 0.01 |
Feature set partitioning generalizes the task of feature selection by partitioning the feature set into subsets of features that are collectively useful, rather than by finding a single useful subset of features. This paper presents a novel feature set partitioning approach that is based on a genetic algorithm. As part of this new approach a new encoding schema is also proposed and its properties are discussed. We examine the effectiveness of using a Vapnik-Chervonenkis dimension bound for evaluating the fitness function of multiple, oblivious tree classifiers. The new algorithm was tested on various datasets and the results indicate the superiority of the proposed algorithm to other methods.