Deep Generative Models to Counter Class Imbalance: A Model-Metric Mapping With Proportion Calibration Methodology

Deep Generative Models to Counter Class Imbalance: A Model-Metric Mapping With Proportion Calibration Methodology

The most pervasive segment of techniques in managing class imbalance in machine learning are re-sampling-based methods. The emergence of deep generative models for augmenting the size of the under-represented class, prompts one to review the question of the suitability of the model chosen for data a...

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Bibliographic Details
Main Authors: Behroz Mirza, Danish Haroon, Behraj Khan, Ali Padhani, Tahir Q. Syed
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Adversarial networks
anomaly detection
class imbalance
deep generative models
density estimation
generative variational auto encoders
Online Access:https://ieeexplore.ieee.org/document/9395632/

Internet

https://ieeexplore.ieee.org/document/9395632/

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