By Tamás Kenesei,János Abonyi
The key inspiration of this publication is that hinging hyperplanes, neural networks and help vector machines may be remodeled into fuzzy versions, and interpretability of the ensuing rule-based structures should be ensured by way of certain version aid and visualization suggestions. the 1st a part of the booklet bargains with the identity of hinging hyperplane-based regression bushes. the following half bargains with the validation, visualization and structural aid of neural networks according to the transformation of the hidden layer of the community into an additive fuzzy rule base approach. ultimately, in response to the analogy of aid vector regression and fuzzy versions, a three-step version relief set of rules is proposed to get interpretable fuzzy regression types at the foundation of aid vector regression.
The authors show real-world use of the algorithms with examples taken from procedure engineering, they usually help the textual content with downloadable Matlab code. The e-book is appropriate for researchers, graduate scholars and practitioners within the components of computational intelligence and computing device learning.
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