International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Decision trees and multi-valued attributes
Machine intelligence 11
Criteria for Selecting a Variable in the Construction of Efficient Decision Trees
IEEE Transactions on Computers
ACM Computing Surveys (CSUR)
Machine Learning
A Machine Learning Approach to POS Tagging
Machine Learning
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
IEEE Transactions on Knowledge and Data Engineering
Simplifying decision trees: A survey
The Knowledge Engineering Review
Applying machine learning to Chinese temporal relation resolution
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Interestingness of Association Rules Using Symmetrical Tau and Logistic Regression
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
Adaptation knowledge from the case base
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Focusing solutions for data mining: analytical studies and experimental results in real-world domains
A statistical interestingness measures for XML based association rules
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Interestingness measures for association rules based on statistical validity
Knowledge-Based Systems
An integration of biometrics and mobile computing for personal identification
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Feature selection method using preferences aggregation
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
Expert Systems with Applications: An International Journal
White box radial basis function classifiers with component selection for clinical prediction models
Artificial Intelligence in Medicine
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The authors present a statistical-heuristic feature selection criterion for constructing multibranching decision trees in noisy real-world domains. Real world problems often have multivalued features. To these problems, multibranching decision trees provide a more efficient and more comprehensible solution that binary decision trees. The authors propose a statistical-heuristic criterion, the symmetrical tau and then discuss its consistency with a Bayesian classifier and its built-in statistical test. The combination of a measure of proportional-reduction-in-error and cost-of-complexity heuristic enables the symmetrical tau to be a powerful criterion with many merits, including robustness to noise, fairness to multivalued features, and ability to handle a Boolean combination of logical features, and middle-cut preference. The tau criterion also provides a natural basis for prepruning and dynamic error estimation. Illustrative examples are also presented.