Domains of Competence of Artificial Neural Networks Using Measures of Separability of Classes
作者： Julián Luengo , Francisco Herrera
DOI: 10.1007/978-3-642-02478-8_11
关键词:
摘要: In this work we want to analyse the behaviour of two classic Artificial Neural Network models respect a data complexity measures. particular, consider Radial Basis Function and Multi-Layer Perceptron. We examine metrics known as Measures Separability Classes over wide range sets built from real data, try extract patterns results. obtain rules that describe both good or bad behaviours Networks mentioned. With obtained rules, predict methods set prior its application, therefore establish their domains competence.
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