CCR: a combined cleaning and resampling algorithm for imbalanced data classification

DOI10.1515/amcs-2017-0050zbMath1396.68097DBLPjournals/amcs/KoziarskiW17OpenAlexW2783151797WikidataQ62630316 ScholiaQ62630316MaRDI QIDQ1787035

Michał Koziarski, Michał Woźniak

Publication date: 26 September 2018

Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/amcs-2017-0050

zbMATH Keywords

classificationmachine learningoversamplingpreprocessingimbalanced data

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Fusion of clinical data: a case study to predict the type of treatment of bone fractures ⋮ RB-CCR: radial-based combined cleaning and resampling algorithm for imbalanced data classification

Uses Software

• JStatCom
• Scikit
• SMOTEBoost
• Imbalanced-learn
• ROSEFW-RF
• MWMOTE
• SMOTE
• ADASYN
• ACOSampling

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Iterative Boolean combination of classifiers in the ROC space: an application to anomaly detection with HMMs
• A dynamic over-sampling procedure based on sensitivity for multi-class problems
• Two Modifications of CNN
• Asymptotic Properties of Nearest Neighbor Rules Using Edited Data

This page was built for publication: CCR: a combined cleaning and resampling algorithm for imbalanced data classification