C4.5: programs for machine learning
C4.5: programs for machine learning
Variable precision rough set model
Journal of Computer and System Sciences
The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Communications of the ACM
Uncertainly measures of rough set prediction
Artificial Intelligence
Information Sciences: an International Journal
Rules in incomplete information systems
Information Sciences: an International Journal
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
The algorithm on knowledge reduction in incomplete information systems
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Data Mining and Knowledge Discovery
Discretization: An Enabling Technique
Data Mining and Knowledge Discovery
An Instance-Weighting Method to Induce Cost-Sensitive Trees
IEEE Transactions on Knowledge and Data Engineering
Rough sets and intelligent data analysis
Information Sciences—Informatics and Computer Science: An International Journal
A General Two-Stage Approach to Inducing Rules from Examples
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Learning and Making Decisions When Costs and Probabilities are Both Unknown
Learning and Making Decisions When Costs and Probabilities are Both Unknown
Approaches to knowledge reduction based on variable precision rough set model
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
Mining with rarity: a unifying framework
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
A study of the behavior of several methods for balancing machine learning training data
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Mining diagnostic rules from clinical databases using rough sets and medical diagnostic model
Information Sciences: an International Journal - Special issue: Medical expert systems
Training Cost-Sensitive Neural Networks with Methods Addressing the Class Imbalance Problem
IEEE Transactions on Knowledge and Data Engineering
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
A Comparative Study of Algebra Viewpoint and Information Viewpoint in Attribute Reduction
Fundamenta Informaticae
Rough Sets for Handling Imbalanced Data: Combining Filtering and Rule-based Classifiers
Fundamenta Informaticae - SPECIAL ISSUE ON CONCURRENCY SPECIFICATION AND PROGRAMMING (CS&P 2005) Ruciane-Nide, Poland, 28-30 September 2005
The class imbalance problem: A systematic study
Intelligent Data Analysis
A weighted rough set based method developed for class imbalance learning
Information Sciences: an International Journal
Posterior probability support vector Machines for unbalanced data
IEEE Transactions on Neural Networks
Fundamenta Informaticae
Rough set approach to online signature identification
Digital Signal Processing
Fuzzy rough set based attribute reduction for information systems with fuzzy decisions
Knowledge-Based Systems
Class imbalance methods for translation initiation site recognition in DNA sequences
Knowledge-Based Systems
Comparing alternative classifiers for database marketing: The case of imbalanced datasets
Expert Systems with Applications: An International Journal
Dynamic classifier ensemble model for customer classification with imbalanced class distribution
Expert Systems with Applications: An International Journal
Instance selection for class imbalanced problems by means of selecting instances more than once
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
A new weighted rough set framework based classification for Egyptian NeoNatal Jaundice
Applied Soft Computing
Graded rough set model based on two universes and its properties
Knowledge-Based Systems
Identifying the medical practice after total hip arthroplasty using an integrated hybrid approach
Computers in Biology and Medicine
A hybrid generative/discriminative method for semi-supervised classification
Knowledge-Based Systems
Class imbalance and the curse of minority hubs
Knowledge-Based Systems
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This paper performs systematic comparative studies on rough set based class imbalance learning. We compare the strategies of weighting, re-sampling and filtering used in the rough set based methods for class imbalance learning. Weighting is better than re-sampling, and re-sampling is better than filtering. The weighted rough set based method achieves the best performance in class imbalance learning. Furthermore, we compare various configurations of the weighted rough set based method. The weighted rule extraction and weighted decision have greater influence on the performance of the weighted rough set based method than the weighted attribute reduction. The weighted attribute reduction based on the weighted degree of dependency, the rule extraction for the exhaustive set of rules and the weighted decision based on the majority voting of the factor of weighted strength are the optimal configurations for class imbalance learning. Finally, we compare the weighted rough set based method with the decision tree and SVM based methods. The experimental results show that the weighted rough set based method outperforms the decision tree and SVM based methods. It can be concluded from the comparisons that the weighted rough set based method is effective for class imbalance learning.