Hypothesis-Driven Constructive Induction in AQ17-HCI: A Method and Experiments
Machine Learning - Special issue on evaluating and changing representation
Continuous case-based reasoning
Artificial Intelligence
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Requirements for Successful Verification in Practice
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
Logical Foundations for Rule-Based Systems (Studies in Computational Intelligence) (Studies in Computational Intelligence)
Post-processing of associative classification rules using closed sets
Expert Systems with Applications: An International Journal
ICDM'11 Proceedings of the 11th international conference on Advances in data mining: applications and theoretical aspects
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The main goal of our research was to compile new methodology for building simplified learning models in a form of decision rule set. Every investigated source informational dataset was extended by application of constructive induction method to get a new, additional, descriptive attribute, and then sets of decision rules were developed for source and for extended database, respectively. In the last step, obtained set of rules were optimized and compared to earlier set of rules.