DocumentCode
3426461
Title
Data mining with ensembles of fuzzy decision trees
Author
Marsala, Christophe
Author_Institution
LIP6, Univ. Pierre et Marie Curie Paris 6, Paris
fYear
2009
fDate
March 30 2009-April 2 2009
Firstpage
348
Lastpage
354
Abstract
In this paper, a study is presented to explore ensembles of fuzzy decision trees. First of all, a quick recall of the state of the art related to ensembles of (fuzzy) decision trees in Machine Learning is presented. Afterwards, a new approach to construct a forest of fuzzy decision trees is proposed. Two experiments are described, one with forests of fuzzy decision trees, and the other with bagging of fuzzy decision trees. The results highlight the interest of using fuzzy set theory in this kind of approaches.
Keywords
data mining; decision trees; fuzzy set theory; learning (artificial intelligence); data mining; fuzzy decision trees; machine learning; Bagging; Boosting; Classification tree analysis; Data mining; Decision trees; Error analysis; Fuzzy set theory; Machine learning; Machine learning algorithms; Probability;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Data Mining, 2009. CIDM '09. IEEE Symposium on
Conference_Location
Nashville, TN
Print_ISBN
978-1-4244-2765-9
Type
conf
DOI
10.1109/CIDM.2009.4938670
Filename
4938670
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