C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
Machine Learning
Classification with Nominal Data Using Intuitionistic Fuzzy Sets
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
Rule Extraction and Reduction for Hyper Surface Classification
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
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In this paper an algorithm is proposed for the extraction of rules from decision trees for nominal data that could be even in the form of free text. The goal of the algorithm is to process a decision tree generated as input, using the classification algorithm ID3 (Quinlan, 1986, 1993), and to extract rules expressed in natural language. The input tree in this case is full of complex nominal expressions in the form of free text. The whole system is tested with two examples taken from the field of stock market news and medical knowledge.