Zero-Inflated Binary Classification Model with Elastic Net Regularization

Zero-Inflated Binary Classification Model with Elastic Net Regularization

Zero inflation and overfitting can reduce the accuracy rate of using machine learning models for characterizing binary data sets. A zero-inflated Bernoulli (ZIBer) model can be the right model to characterize zero-inflated binary data sets. When the ZIBer model is used to characterize zero-inflated...

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Bibliographic Details
Main Authors: Hua Xin, Yuhlong Lio, Hsien-Ching Chen, Tzong-Ru Tsai
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Mathematics
Subjects:
expectation-maximization algorithm
gradient descent method
learning rate
maximum likelihood estimation
zero-inflated model
Online Access:https://www.mdpi.com/2227-7390/12/19/2990

Internet

https://www.mdpi.com/2227-7390/12/19/2990

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