Roughly balanced bagging for imbalanced data

DOI10.1002/SAM.10061MaRDI QIDQ6641624

Yutaka Takahashi, Shohei Hido, Hisashi Kashima

Publication date: 21 November 2024

Published in: Statistical Analysis and Data Mining (Search for Journal in Brave)

zbMATH Keywords

resamplingnegative binomial distributionbaggingimbalanced data

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Cites Work

• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Bagging predictors
• On bagging and nonlinear estimation
• A decision-theoretic generalization of on-line learning and an application to boosting
• Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy
• Analyzing bagging
• The use of ranks to avoid the assumption of normality implicit in the analysis of variance.
• Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach
• Random forests

Related Items (1)

Using weight reliability masks on imbalanced datasets for satellite image segmentation

This page was built for publication: Roughly balanced bagging for imbalanced data

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6641624)