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Machine Learning for Mining Imbalanced Data
(2018-02-19)
Mining imbalanced data, which is also known as class imbalanced problem is one of the most enormous challenging tasks in machine learning for data mining applications. To achieve overall accurate performance in imbalanced ...
Cluster-Based Under-Sampling with Random Forest for Multi-Class Imbalanced Classification
(2018-02-19)
Multi-class imbalanced classification has emerged as a very challenging re- search area in machine learning for data mining applications. It occurs when the number of training instances representing majority class instances ...
A Feature Group Weighting Method for Classifying High-Dimensional Big Data
(2019-11-25)
Features hold the distinctive characteristics and intrinsic values of data. But it's of
no use if the important information and pattern can not be extracted from the data
coming from disparate sources and applications. ...
Customer Churn Analysis Using Association Rule Mining and Decision Tree Classifiers
(2021-12)
Customer churn is a prominent issue facing companies. Therefore, preventing customer churn and retaining and retaining customers has become an essential issue for business operations and development. This paper aims to ...