Abstract
In the paper is discussed the truncated nondeterministic rules and their role in an evaluation of classification model. The nondeterministic rules are created as the result of shorting deterministic rules in accordance with the principle of minimum description length (MDL). As deterministic rules in database we treat the full objects description in a meaning of descriptors conjunction. The nondeterministic rules are calculated in polynomial time by using greedy strategy.
The classification model is composed in two steps process. In the first step deterministic and nondeterministic rules are constructed. Next these rules are used for classifier evaluation. The evaluation results are compared with classifiers only based on deterministic rules creating by different algorithms. The experiments shows that such nondeterministic rules could be treat as an extra knowledge about data. This knowledge is able to improve the classification quality. It should be pointed out that classification process requires tuning some of their parameters relative to analyzed data.
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Paszek, P., Marszał-Paszek, B. (2014). Nondeterministic Decision Rules in Rule-Based Classifier. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures, and Structures. BDAS 2014. Communications in Computer and Information Science, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-06932-6_18
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DOI: https://doi.org/10.1007/978-3-319-06932-6_18
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