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Computer Science

Sampling Approaches for Imbalanced Data Classification Problem in Machine Learning

S. Tyagi, Sangeeta Mittal

2019Lecture Notes in Electrical Engineering

DOI: 10.1007/978-3-030-29407-6_17

tlooto Summary

It has been observed that adaptive synthetic oversampling approach can best improve the imbalance ratio as well as classification results, however, undersampling approaches gave better overall performance on all datasets.

Abstract

Abstract is not available.

Citation format

TYAGI, S.; MITTAL, Sangeeta. Sampling approaches for imbalanced data classification problem in machine learning. Lecture Notes in Electrical Engineering, 2019.