Learning from Imbalanced Data Using Ensemble Methods and Cluster-Based Undersampling

Parinaz Sobhani; Herna L. Viktor; Stan Matwin

doi:10.1007/978-3-319-17876-9_5

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Learning from Imbalanced Data Using Ensemble Methods and Cluster-Based Undersampling

Parinaz Sobhani Herna L. Viktor Stan Matwin

Year: 2015 Lecture notes in computer science Pages: 69-83 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-17876-9_5

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Keywords:

Undersampling Computer science Class (philosophy) Artificial intelligence Cluster (spacecraft) Machine learning Data mining Pattern recognition (psychology)

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Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Electricity Theft Detection Techniques

Physical Sciences → Engineering → Electrical and Electronic Engineering

Machine Learning and Data Classification

Physical Sciences → Computer Science → Artificial Intelligence

Learning from Imbalanced Data Using Ensemble Methods and Cluster-Based Undersampling

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