Journal ArticleDOI
Fuzzy SLIQ Decision Tree Algorithm
B. Chandra,P.P. Varghese +1 more
- Vol. 38, Iss: 5, pp 1294-1301
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TLDR
The proposed fuzzy supervised learning in Quest (SLIQ) decision tree (FS-DT) algorithm is aimed at constructing a fuzzy decision boundary instead of a crisp decision boundary, which results in more than 70% reduction in size of the decision tree compared to SLIQ.Abstract:
Traditional decision tree algorithms face the problem of having sharp decision boundaries which are hardly found in any real-life classification problems. A fuzzy supervised learning in Quest (SLIQ) decision tree (FS-DT) algorithm is proposed in this paper. It is aimed at constructing a fuzzy decision boundary instead of a crisp decision boundary. Size of the decision tree constructed is another very important parameter in decision tree algorithms. Large and deeper decision tree results in incomprehensible induction rules. The proposed FS-DT algorithm modifies the SLIQ decision tree algorithm to construct a fuzzy binary decision tree of significantly reduced size. The performance of the FS-DT algorithm is compared with SLIQ using several real-life datasets taken from the UCI Machine Learning Repository. The FS-DT algorithm outperforms its crisp counterpart in terms of classification accuracy. FS-DT also results in more than 70% reduction in size of the decision tree compared to SLIQ.read more
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Extraction of fuzzy rules from fuzzy decision trees: An axiomatic fuzzy sets (AFS) approach
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Journal ArticleDOI
Geometric Decision Tree
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References
More filters
Journal ArticleDOI
Classification and Regression Trees.
Journal ArticleDOI
Induction of Decision Trees
TL;DR: In this paper, an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, is described, and a reported shortcoming of the basic algorithm is discussed.
Book
Classification and regression trees
TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
Journal ArticleDOI
Programs for machine learning Part I
TL;DR: A proposed schema and some detailed specifications for constructing a learning system by means of programming a computer are given, trying to separate learning processes and problem-solving techniques from specific problem content in order to achieve generality.
Journal ArticleDOI
A survey of decision tree classifier methodology
S.R. Safavian,David A. Landgrebe +1 more
TL;DR: The subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed, and the relation between decision trees and neutral networks (NN) is also discussed.