Prediction of a Class Variable in Classification Problem Using Fuzzy Inference Method

Authors

  • S.V.S. Ganga Devi K.S.R.M. College of Engineering, Kadapa – 516003, A.P., India

Keywords:

Fuzzy Technique

Abstract

A popular and particularly efficient method for making a decision tree for classification from symbolic data is ID3 algorithm. Revised algorithms for numerical data have been proposed, some of which divide a numerical range into several intervals or fuzzy intervals. Their decision trees, however, are not easy to understand. A new version of ID3 algorithm to generate a understandable fuzzy decision tree using fuzzy sets defined by a user. In this paper, first the fuzzy decision tree is constructed for the given data and then fuzzy reasoning is applied in order to predict the class variable.

References

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Published

2014-01-31

How to Cite

[1]
S. G. Devi, “Prediction of a Class Variable in Classification Problem Using Fuzzy Inference Method”, Int. J. Comp. Sci. Eng., vol. 2, no. 1, pp. 28–29, Jan. 2014.

Issue

Vol. 2 No. 1 (2014): IJCSE January Edition

Section

Research Article

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