Improving logistic regression on the imbalanced data by a novel penalized log-likelihood function

DOI10.1080/02664763.2021.1939662OpenAlexW3176376866MaRDI QIDQ5044639

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Publication date: 2 November 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2021.1939662

zbMATH Keywords

maximum likelihoodlogistic regressionbinary classificationcost-sensitiveimbalanced datapenalized log-likelihood function

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Related Items

Finding the proverbial needle: improving minority class identification under extreme class imbalance

Uses Software

• Scikit
• aplore3

Cites Work

• Robust weighted kernel logistic regression in imbalanced and rare events data
• Kernel logistic regression using truncated Newton method
• A New Estimator for a Population Proportion Using Group Testing
• Applied Logistic Regression
• A descriptive study of variable discretization and cost-sensitive logistic regression on imbalanced credit data
• Imbalanced Learning
• Structural, Syntactic, and Statistical Pattern Recognition
• Estimation of the probability of an event as a function of several independent variables
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