Abstract
The main goal of presented research was to compile new approach for development learning models in a form of decision rule set. This approach devotes to using primary decision table as a primitive set of rules. Thus, each of learning cases is treated as a single classification rule. Next, a set of generic operations are applied to find the final, qualitative learning model. These generic operations are implemented in the RuleSEEKER system. During this research a few well-known algorithm for rule generation were compared with proposed solution. Obtained results are similar, sometimes even better and suggests that this method is a promising solution.
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Paja, W., Wrzesień, M. (2012). Decision Rules Development Using Set of Generic Operations Approach. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2012. Lecture Notes in Computer Science(), vol 7377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31488-9_19
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DOI: https://doi.org/10.1007/978-3-642-31488-9_19
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