The New Approach on Fuzzy Decision Trees
Artificial Intelligence
2014-08-14 v1
Abstract
Decision trees have been widely used in machine learning. However, due to some reasons, data collecting in real world contains a fuzzy and uncertain form. The decision tree should be able to handle such fuzzy data. This paper presents a method to construct fuzzy decision tree. It proposes a fuzzy decision tree induction method in iris flower data set, obtaining the entropy from the distance between an average value and a particular value. It also presents an experiment result that shows the accuracy compared to former ID3.
Keywords
Cite
@article{arxiv.1408.3002,
title = {The New Approach on Fuzzy Decision Trees},
author = {Jooyeol Yun and Jun won Seo and Taeseon Yoon},
journal= {arXiv preprint arXiv:1408.3002},
year = {2014}
}