Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
Variable Precision Rough Sets with Asymmetric Bounds
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Fundamentals of Information Theory and Coding Design
Fundamentals of Information Theory and Coding Design
Consistency-based search in feature selection
Artificial Intelligence
Efficient Feature Selection via Analysis of Relevance and Redundancy
The Journal of Machine Learning Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Dependency and Correlation Analysis for Features
IEEE Transactions on Knowledge and Data Engineering
A hybrid approach for feature subset selection using neural networks and ant colony optimization
Expert Systems with Applications: An International Journal
A hybrid genetic algorithm for feature selection wrapper based on mutual information
Pattern Recognition Letters
Computers & Mathematics with Applications
Probabilistic approach to rough sets
International Journal of Approximate Reasoning
Feature selection with dynamic mutual information
Pattern Recognition
Estimating Optimal Feature Subsets Using Mutual Information Feature Selector and Rough Sets
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Advanced Engineering Informatics
A rough set approach to feature selection based on ant colony optimization
Pattern Recognition Letters
The investigation of the Bayesian rough set model
International Journal of Approximate Reasoning
Analysis on classification performance of rough set based reducts
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Integrated feature architecture selection
IEEE Transactions on Neural Networks
Neural-network feature selector
IEEE Transactions on Neural Networks
Input feature selection for classification problems
IEEE Transactions on Neural Networks
Feature selection in MLPs and SVMs based on maximum output information
IEEE Transactions on Neural Networks
Using mutual information for selecting features in supervised neural net learning
IEEE Transactions on Neural Networks
Fast feature selection aimed at high-dimensional data via hybrid-sequential-ranked searches
Expert Systems with Applications: An International Journal
Knowledge reduction for decision tables with attribute value taxonomies
Knowledge-Based Systems
Multi-level rough set reduction for decision rule mining
Applied Intelligence
Mutual information evaluation: A way to predict the performance of feature weighting on clustering
Intelligent Data Analysis
| Hi-index | 12.05 |
In this paper, we introduced a novel feature selection method based on the hybrid model (filter-wrapper). We developed a feature selection method using the mutual information criterion without requiring a user-defined parameter for the selection of the candidate feature set. Subsequently, to reduce the computational cost and avoid encountering to local maxima of wrapper search, a wrapper approach searches in the space of a superreduct which is selected from the candidate feature set. Finally, the wrapper approach determines to select a proper feature set which better suits the learning algorithm. The efficiency and effectiveness of our technique is demonstrated through extensive comparison with other representative methods. Our approach shows an excellent performance, not only high classification accuracy, but also with respect to the number of features selected.