A Relevancy Filter for Constructive Induction
IEEE Intelligent Systems
Applying Noise Handling Techniques to Genomic Data: A Case Study
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Determining noisy instances relative to attributes of interest
Intelligent Data Analysis
The pairwise attribute noise detection algorithm
Knowledge and Information Systems - Special Issue on Mining Low-Quality Data
Enhancing software quality estimation using ensemble-classifier based noise filtering
Intelligent Data Analysis
Identifying noisy features with the Pairwise Attribute Noise Detection Algorithm
Intelligent Data Analysis
Evaluating noise elimination techniques for software quality estimation
Intelligent Data Analysis
An algorithm for correcting mislabeled data
Intelligent Data Analysis
Improving software quality prediction by noise filtering techniques
Journal of Computer Science and Technology
Noise elimination with partitioning filter for software quality estimation
International Journal of Computer Applications in Technology
Class Noise Mitigation Through Instance Weighting
ECML '07 Proceedings of the 18th European conference on Machine Learning
Software quality analysis by combining multiple projects and learners
Software Quality Control
Class noise detection using frequent itemsets
Intelligent Data Analysis
Empirical case studies in attribute noise detection
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Assessing the quality and cleaning of a software project dataset: an experience report
EASE'06 Proceedings of the 10th international conference on Evaluation and Assessment in Software Engineering
Preceding rule induction with instance reduction methods
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
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