Ensembles of Classifiers in Arrears Management

DOI10.1007/978-3-540-79005-1_1zbMath1153.62366OpenAlexW1547904539MaRDI QIDQ5302330

Esther Scheurmann, Chris Matthews

Publication date: 7 January 2009

Published in: Soft Computing Applications in Business (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-79005-1_1

zbMATH Keywords

arrears managementdata set imbalanceloan defaultneural network and rule based ensembles

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to actuarial sciences and financial mathematics (62P05) Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• A comparison of neural networks and linear scoring models in the credit union environment
• Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy
• Neural network credit scoring models
• Neural network ensembles: evaluation of aggregation algorithms
• Comparing a genetic fuzzy and a neurofuzzy classifier for credit scoring
• Neural network survival analysis for personal loan data

This page was built for publication: Ensembles of Classifiers in Arrears Management