Anzeige
Erschienen in:
2003 | OriginalPaper | Buchkapitel
Constrained Optimization of Fuzzy Decision Trees
verfasst von : Pierre-Yves Glorennec
Erschienen in: Interpretability Issues in Fuzzy Modeling
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
This paper proposes to build and optimize Takagi-Sugeno-like fuzzy regression trees with constraints aiming at preserving the interpretability of the rules. For this purpose, we state five requirements and deduce some conditions such as membership functions shared by the rules and strong fuzzy partitions on input variable domains. The membership functions are automatically placed thanks to an evolutionary strategy. We propose also a heuristics in order to find a sub-optimal structure of the tree.