The maximum likelihood neural network as a statistical classification model

DOI10.1016/0378-3758(95)99068-2zbMath0821.62034OpenAlexW2018900194MaRDI QIDQ1895375

David Faraggi, Richard M. Simon

Publication date: 3 October 1995

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(95)99068-2

zbMATH Keywords

classificationlikelihood ratio testmaximum likelihoodfeed-forward neural networkAkaike criterionmultinomial caselogistic likelihood functionnonlinear multivariate classifier

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

Unnamed Item ⋮ Unnamed Item ⋮ Comparison of the performance of neural network methods and Cox regression for censored survival data.

Cites Work

• Generalized additive models
• Neural networks: A review from a statistical perspective. With comments and a rejoinder by the authors
• Hierarchical clustering schemes
• Printer graphics for clustering
• Some Asymptotic Results for Learning in Single Hidden-Layer Feedforward Network Models
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