Fundamentals for Design and Construction of a Fuzzy Random Forest

被引：0

作者：

Bonissone, Piero P. ^{[1
]}

Manuel Cadenas, Jose ^{[2
]}

del Carmen Garrido, Maria ^{[2
]}

Andres Diaz-Valladares, R. ^{[3
]}

机构：

[1] GE Global Res, 1 Res Circle, Niskayuna, NY 12309 USA

[2] Univ Murcia, Dept Imgenieria Infromat Commun, Murcia, Spain

[3] Univ Montemorelos, Dept Ciencias Computacionales, Montemorelos, Mexico

来源：

FOUNDATIONS OF REASONING UNDER UNCERTAINTY | 2010年 / 249卷

关键词：

Approximate Reasoning; Fuzzy Decision Trees; Random Forest; Combination Methods; COMBINING CLASSIFIERS; DECISION TREES; CLASSIFICATION; ENSEMBLES;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Following Breiman's methodology, we propose the fundamentals to design and construct a "forest" of randomly generated fuzzy decision trees, i.e., a Fuzzy Random Forest. This approach combines the robustness of multi-classifiers, the construction efficiency of decision trees, the power of the randomness to increase the diversity of the trees in the forest, and the flexibility of fuzzy logic and the fuzzy sets for data managing. A prototype for the method has been constructed and we have implemented some specific strategies for inference in the Fuzzy Random Forest. Some experimental results are given.

引用

页码：23 / +

页数：3

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