Probability Logic and Optimization SAT: The PSAT and CPA Models
Annals of Mathematics and Artificial Intelligence
A New Text Categorization Technique Using Distributional Clustering and Learning Logic
IEEE Transactions on Knowledge and Data Engineering
Logic classification and feature selection for biomedical data
Computers & Mathematics with Applications
Efficient Text Classification Using Best Feature Selection and Combination of Methods
Proceedings of the Symposium on Human Interface 2009 on ConferenceUniversal Access in Human-Computer Interaction. Part I: Held as Part of HCI International 2009
Improved Comprehensibility and Reliability of Explanations via Restricted Halfspace Discretization
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Discretization of Target Attributes for Subgroup Discovery
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
The Needles-in-Haystack Problem
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Logic based methods for SNPs tagging and reconstruction
Computers and Operations Research
Logic mining for financial data
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
Review: Supervised classification and mathematical optimization
Computers and Operations Research
Hi-index | 0.00 |
This paper describes a method for learning logic relationships that correctly classify a given data set. The method derives from given logic data certain minimum cost satisfiability problems, solves these problems, and deduces from the solutions the desired logic relationships. Uses of the method include data mining, learning logic in expert systems, and identification of critical characteristics for recognition systems. Computational tests have proved that the method is fast and effective.