C4.5: programs for machine learning
C4.5: programs for machine learning
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Machine Learning
Fril- Fuzzy and Evidential Reasoning in Artificial Intelligence
Fril- Fuzzy and Evidential Reasoning in Artificial Intelligence
Machine Learning
Tree Induction for Probability-Based Ranking
Machine Learning
A complete fuzzy decision tree technique
Fuzzy Sets and Systems - Theme: Learning and modeling
A framework for linguistic modelling
Artificial Intelligence
Fuzzy decision trees: issues and methods
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
Fuzziness and Performance: An Empirical Study with Linguistic Decision Trees
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
Fuzzifying Gini Index based decision trees
Expert Systems with Applications: An International Journal
Fuzzy Sets and Systems
Granular knowledge representation and inference using labels and label expressions
IEEE Transactions on Fuzzy Systems - Special section on computing with words
A prototype-based rule inference system incorporating linear functions
Fuzzy Sets and Systems
Minority game data mining for stock market predictions
ADMI'10 Proceedings of the 6th international conference on Agents and data mining interaction
Prediction and query evaluation using linguistic decision trees
Applied Soft Computing
Behavior learning in minority games
CARE@AI'09/CARE@IAT'10 Proceedings of the CARE@AI 2009 and CARE@IAT 2010 international conference on Collaborative agents - research and development
A balanced neural tree for pattern classification
Neural Networks
Hybrid bayesian estimation trees based on label semantics
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A linguistic decision tree approach to predicting storm surge
Fuzzy Sets and Systems
Decision trees: a recent overview
Artificial Intelligence Review
Hybrid Bayesian estimation tree learning with discrete and fuzzy labels
Frontiers of Computer Science: Selected Publications from Chinese Universities
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Label semantics is a random set based framework for ''Computing with Words'' that captures the idea of computation on linguistic terms rather than numerical quantities. Within this new framework, a decision tree learning model is proposed where nodes are linguistic descriptions of variables and leaves are sets of appropriate labels. In such decision trees, the probability estimates for branches across the whole tree is used for classification, instead of the majority class of the single branch into which the examples fall. By empirical experiments on real-world datasets it is verified that our algorithm has better or equivalent classification accuracy compared to three well known machine learning algorithms. By applying a new forward branch merging algorithm, the complexity of the tree can be greatly reduced without significant loss of accuracy. Finally, a linguistic interpretation of trees and classification with linguistic constraints are introduced.