Logistic regression using covariates obtained by product-unit neural network models

DOI10.1016/j.patcog.2006.06.003zbMath1103.68689OpenAlexW2109527845MaRDI QIDQ853094

N. E. Zubov

Publication date: 15 November 2006

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2006.06.003

zbMATH Keywords

classificationlogistic regressionproduct-unit neural network

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

Logistic evolutionary product-unit neural networks: Innovation capacity of poor Guatemalan households ⋮ Probability estimation for multi-class classification using adaboost ⋮ Multilogistic regression by means of evolutionary product-unit neural networks

Uses Software

• UCI-ml
• ElemStatLearn
• C4.5

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Optimization by Simulated Annealing
• Multivariate adaptive regression splines
• Neural networks and logistic regression: Part I
• Neural networks and logistic regression. II.
• Additive logistic regression: a statistical view of boosting. (With discussion and a rejoinder by the authors)
• Data mining and knowledge discovery with evolutionary algorithms
• Evolutionary product unit based neural networks for regression
• On the Complexity of Computing and Learning with Multiplicative Neural Networks
• Partial BFGS Update and Efficient Step-Length Calculation for Three-Layer Neural Networks
• Best Subsets Logistic Regression
• Logistic disease incidence models and case-control studies
• A Bayesian Approach to Nonparametric Bivariate Regression
• Functional trees
• Logistic model trees
• The elements of statistical learning. Data mining, inference, and prediction

This page was built for publication: Logistic regression using covariates obtained by product-unit neural network models