Variable precision rough set model
Journal of Computer and System Sciences
Using Rough Sets with Heuristics for Feature Selection
Journal of Intelligent Information Systems
Machine Learning
Rough set methods in feature selection and recognition
Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
Fundamenta Informaticae
An introduction to variable and feature selection
The Journal of Machine Learning Research
Consistency-based search in feature selection
Artificial Intelligence
Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough-Based Approaches
IEEE Transactions on Knowledge and Data Engineering
Toward Integrating Feature Selection Algorithms for Classification and Clustering
IEEE Transactions on Knowledge and Data Engineering
On fuzzy-rough sets approach to feature selection
Pattern Recognition Letters
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Pattern Recognition Letters
Analysis on classification performance of rough set based reducts
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Improved feature selection algorithm based on SVM and correlation
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Selecting discrete and continuous features based on neighborhood decision error minimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new credit scoring method based on rough sets and decision tree
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Stability analysis on rough set based feature evaluation
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Feature Selection via Maximizing Fuzzy Dependency
Fundamenta Informaticae
Research on rough set theory and applications in China
Transactions on rough sets VIII
A new knowledge reduction algorithm based on decision power in rough set
Transactions on rough sets XII
The Knowledge Engineering Review
Expert Systems with Applications: An International Journal
A bit-chain based algorithm for problem of attribute reduction
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
Minimum cost attribute reduction in decision-theoretic rough set models
Information Sciences: an International Journal
Related family: A new method for attribute reduction of covering information systems
Information Sciences: an International Journal
Feature Reduction with Inconsistency
International Journal of Cognitive Informatics and Natural Intelligence
| Hi-index | 0.00 |
Rough sets are widely used in feature subset selection and attribute reduction. In most of the existing algorithms, the dependency function is employed to evaluate the quality of a feature subset. The disadvantages of using dependency are discussed in this paper. And the problem of forward greedy search algorithm based on dependency is presented. We introduce the consistency measure to deal with the problems. The relationship between dependency and consistency is analyzed. It is shown that consistency measure can reflects not only the size of decision positive region, like dependency, but also the sample distribution in the boundary region. Therefore it can more finely describe the distinguishing power of an attribute set. Based on consistency, we redefine the redundancy and reduct of a decision system. We construct a forward greedy search algorithm to find reducts based on consistency. What's more, we employ cross validation to test the selected features, and reduce the overfitting features in a reduct. The experimental results with UCI data show that the proposed algorithm is effective and efficient.