GABoost: A Clustering Based Undersampling Algorithm for Highly Imbalanced Datasets Using Genetic Algorithm

O. A. Ajilisa; V P Jagathyraj; M. K. Sabu

doi:10.1007/978-3-030-16681-6_24

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GABoost: A Clustering Based Undersampling Algorithm for Highly Imbalanced Datasets Using Genetic Algorithm

O. A. Ajilisa V P Jagathyraj M. K. Sabu

Year: 2019 Advances in intelligent systems and computing Pages: 235-246 Publisher: Springer Nature

DOI: 10.1007/978-3-030-16681-6_24

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Keywords:

Undersampling Computer science Cluster analysis Machine learning Artificial intelligence Data mining AdaBoost Preprocessor Algorithm Data pre-processing Data set Genetic algorithm Statistical classification Population-based incremental learning Support vector machine

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Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Electricity Theft Detection Techniques

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Financial Distress and Bankruptcy Prediction

Social Sciences → Business, Management and Accounting → Accounting

GABoost: A Clustering Based Undersampling Algorithm for Highly Imbalanced Datasets Using Genetic Algorithm

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