Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Data-Driven Constructive Induction
IEEE Intelligent Systems
Generating Accurate Rule Sets Without Global Optimization
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Classification Algorithms Based on Linear Combinations of Features
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
A New Version of Rough Set Exploration System
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Reducing Number of Decision Rules by Joining
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Using evolutionary algorithms for the unit testing of object-oriented software
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Hyperplane Aggregation of Dominance Decision Rules
Fundamenta Informaticae - International Conference on Soft Computing and Distributed Processing (SCDP'2002)
A system for induction of oblique decision trees
Journal of Artificial Intelligence Research
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In this paper the new approach to generating oblique decision rules is presented. On the basis of limitations for every oblique decision rules parameters the grid of parameters values is created and then for every node of this grid the oblique condition is generated and its quality is calculated. The best oblique conditions build the oblique decision rule. Conditions are added as long as there are non-covered objects and the limitation of the length of the rule is not exceeded. All rules are generated with the idea of sequential covering.