Mining Incomplete Data—A Comparison of Concept and New Global Probabilistic Approximations

Author:

Clark Patrick G.,Grzymala-Busse Jerzy W.,Mroczek Teresa,Niemiec Rafal

Publisher

Springer Singapore

Reference21 articles.

1. Clark, P.G., Gao, C., Grzymala-Busse, J.W., Mroczek, T., Niemiec, R.: A comparison of concept and global probabilistic approximations based on mining incomplete data. In: Proceedings of ICIST 2018, the International Conference on Information and Software Technologies, pp. 324–335 (2018)

2. Clark, P.G., Grzymala-Busse, J.W.: Experiments on probabilistic approximations. In: Proceedings of the 2011 IEEE International Conference on Granular Computing, pp. 144–149 (2011)

3. Clark, P.G., Grzymala-Busse, J.W.: Experiments on rule induction from incomplete data using three probabilistic approximations. In: Proceedings of the 2012 IEEE International Conference on Granular Computing, pp. 90–95 (2012)

4. Clark, P.G., Grzymala-Busse, J.W.: An experimental comparison of three interpretations of missing attribute values using probabilistic approximations. In: Proceedings of the 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, pp. 77–86 (2013)

5. Clark, P.G., Grzymala-Busse, J.W., Rzasa, W.: Mining incomplete data with singleton, subset and concept approximations. Inf. Sci. 280, 368–384 (2014)

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