Induction of fuzzy decision trees
Fuzzy Sets and Systems
C4.5: Programs for Machine Learning
C4.5: Programs for Machine Learning
Machine Learning
SLIQ: A Fast Scalable Classifier for Data Mining
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
SPRINT: A Scalable Parallel Classifier for Data Mining
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A comparative study on heuristic algorithms for generating fuzzydecision trees
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Fuzzy decision tree induction algorithm is an important way with uncertain information. However, the current fuzzy decision tree algorithms do not systematically consider the impact of different fuzzy levels and simply make uncertainty treatment awareness into the selection of extended properties. To avoiding this problem, this paper establishes a generating Hartley measure model based on cut-standard, subsequently, proposes fuzzy ID3 algorithm based on generating Hartley measure model, finally, the results of the experiments indicates that the model is feasible and effective.