Feedforward Neural Network Construction Using Cross Validation

DOI10.1162/089976601317098565zbMath0986.68874OpenAlexW2020663993WikidataQ52051730 ScholiaQ52051730MaRDI QIDQ2770872

Rudy Setiono

Publication date: 17 June 2002

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/089976601317098565

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies and applications (68U99) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (5)

Reliability prediction for evolutionary product in the conceptual design phase using neural network-based fuzzy synthetic assessment ⋮ An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization ⋮ CORES: fusion of supervised and unsupervised training methods for a multi-class classification problem ⋮ Efficient self-organizing multilayer neural network for nonlinear system modeling ⋮ THEORETICAL FOUNDATIONS AND EXPERIMENTAL RESULTS FOR A HIERARCHICAL CLASSIFIER WITH OVERLAPPING CLUSTERS

Uses Software

• UCI-ml

Cites Work

• Using model trees for classification
• Multilayer feedforward networks are universal approximators
• A Penalty-Function Approach for Pruning Feedforward Neural Networks
• Algorithm 500: Minimization of Unconstrained Multivariate Functions [E4]

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