C4.5: programs for machine learning
C4.5: programs for machine learning
Decision Tree Induction Based on Efficient Tree Restructuring
Machine Learning
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
Machine Learning
Fuzzy decision trees: issues and methods
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
User Modeling and User-Adapted Interaction
An Incremental Fuzzy Decision Tree Classification Method for Mining Data Streams
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
FAW'07 Proceedings of the 1st annual international conference on Frontiers in algorithmics
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Incremental fuzzy decision tree-based network forensic system
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
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We present a new classification algorithm that combines three properties: It generates decision trees, which proved a valuable and intelligible tool for classification and generalization of data; it utilizes fuzzy logic, that provides for a fine grained description of classified items adequate for human reasoning; and it is incremental, allowing rapid alternation of classification and learning of new data. The algorithm generalizes known non-incremental algorithms for top down induction of fuzzy decision trees, as well as known incremental algorithms for induction of decision trees in classical logic. The algorithm is shown to be terminating and to yield results equivalent to the non-incremental version.