Cluster-Based Under-Sampling Using Farthest Neighbour Technique for Imbalanced Datasets

G. Rekha; Amit Kumar Tyagi

doi:10.1007/978-3-030-49339-4_5

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Cluster-Based Under-Sampling Using Farthest Neighbour Technique for Imbalanced Datasets

G. Rekha Amit Kumar Tyagi

Year: 2020 Advances in intelligent systems and computing Pages: 35-44 Publisher: Springer Nature

DOI: 10.1007/978-3-030-49339-4_5

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Keywords:

Classifier (UML) Computer science Artificial intelligence Class (philosophy) Pattern recognition (psychology) Cluster (spacecraft) Sampling (signal processing) Data mining Sample (material) Cluster sampling Machine learning

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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

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Cluster-Based Under-Sampling Using Farthest Neighbour Technique for Imbalanced Datasets

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