Inductive knowledge acquisition: a case study
Proceedings of the Second Australian Conference on Applications of expert systems
IEEE Transactions on Software Engineering
C4.5: programs for machine learning
C4.5: programs for machine learning
Variable precision rough set model
Journal of Computer and System Sciences
Branching on attribute values in decision tree generation
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Information Sciences: an International Journal
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Machine Learning
Rough set methods in feature selection and recognition
Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
Information Sciences—Informatics and Computer Science: An International Journal
Approaches to knowledge reduction based on variable precision rough set model
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
On fuzzy-rough sets approach to feature selection
Pattern Recognition Letters
Particle Swarm Algorithm for Minimal Attribute Reduction of Decision Data Tables
IMSCCS '06 Proceedings of the First International Multi-Symposiums on Computer and Computational Sciences - Volume 2 (IMSCCS'06) - Volume 02
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Pattern Recognition Letters
Information Sciences: an International Journal
Review: Dimensionality reduction based on rough set theory: A review
Applied Soft Computing
Exploring the boundary region of tolerance rough sets for feature selection
Pattern Recognition
New approaches to fuzzy-rough feature selection
IEEE Transactions on Fuzzy Systems
A rough set approach for selecting clustering attribute
Knowledge-Based Systems
Positive approximation: An accelerator for attribute reduction in rough set theory
Artificial Intelligence
The superiority of three-way decisions in probabilistic rough set models
Information Sciences: an International Journal
A rough set approach to multiple dataset analysis
Applied Soft Computing
Rough set analysis on call center metrics
Applied Soft Computing
Neighborhood systems-based rough sets in incomplete information system
Knowledge-Based Systems
A new weighted rough set framework based classification for Egyptian NeoNatal Jaundice
Applied Soft Computing
Approximations and uncertainty measures in incomplete information systems
Information Sciences: an International Journal
Fuzzy probabilistic approximation spaces and their information measures
IEEE Transactions on Fuzzy Systems
Fuzzy Rough Sets: The Forgotten Step
IEEE Transactions on Fuzzy Systems
Fuzzy-Rough Sets Assisted Attribute Selection
IEEE Transactions on Fuzzy Systems
Attributes Reduction Using Fuzzy Rough Sets
IEEE Transactions on Fuzzy Systems
Rough-Set-based timing characteristic analyses of distance protective relay
Applied Soft Computing
Using mutual information for selecting features in supervised neural net learning
IEEE Transactions on Neural Networks
Attribute selection based on a new conditional entropy for incomplete decision systems
Knowledge-Based Systems
Decision rule mining using classification consistency rate
Knowledge-Based Systems
Entropy measures and granularity measures for set-valued information systems
Information Sciences: an International Journal
Rough set approach to incomplete numerical data
Information Sciences: an International Journal
Nullity-based matroid of rough sets and its application to attribute reduction
Information Sciences: an International Journal
Review: Knowledge discovery in medicine: Current issue and future trend
Expert Systems with Applications: An International Journal
Feature subset selection using improved binary gravitational search algorithm
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Tumor classification based on gene expression levels is important for tumor diagnosis. Since tumor data in gene expression contain thousands of attributes, attribute selection for tumor data in gene expression becomes a key point for tumor classification. Inspired by the concept of gain ratio in decision tree theory, an attribute selection method based on fuzzy gain ratio under the framework of fuzzy rough set theory is proposed. The approach is compared to several other approaches on three real world tumor data sets in gene expression. Results show that the proposed method is effective. This work may supply an optional strategy for dealing with tumor data in gene expression or other applications.