Diverse classifier ensemble creation based on heuristic dataset modification

DOI10.1080/02664763.2017.1363163OpenAlexW2747360225MaRDI QIDQ5035729

Karamolah Bagheri-Fard, Hamid Jamalinia, Samad Nejatian, Vahideh Rezaie, Saber Khalouei, Hamid Parvin

Publication date: 22 February 2022

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

Full work available at URL: https://doi.org/10.1080/02664763.2017.1363163

zbMATH Keywords

classificationdiversityartificially created datacombining classifier

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• AdaBoost.MH
• BoosTexter

Cites Work

• Unnamed Item
• Bagging predictors
• Subsemble: an ensemble method for combining subset-specific algorithm fits
• Sparse ensembles using weighted combination methods based on linear programming
• Coevolutionary learning of neural network ensemble for complex classification tasks
• A decision-theoretic generalization of on-line learning and an application to boosting
• BoosTexter: A boosting-based system for text categorization
• Boosting first-order learning
• Combining Pattern Classifiers
• Weighted bagging: a modification of AdaBoost from the perspective of importance sampling
• The elements of statistical learning. Data mining, inference, and prediction
• Random forests

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