Abstract
Rough set theory offers new insight into Bayes’ theorem. It does not refer either to prior or posterior probabilities, inherently associated with Bayesian reasoning, but reveals some probabilistic structure of the data being analyzed. This property can be used directly to draw conclusions from data.
It is also worth mentioning the relationship between Bayes’ theorem and flow graphs.
“I had come to an entirely erroneus conclusions, which shows, my dear Watson, how dangerous it always is to reason from insufficient data”
Sherlock Holmes In: “The speckled band”
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Pawlak, Z. (2003). Bayes’ Theorem — the Rough Set Perspective. In: Inuiguchi, M., Hirano, S., Tsumoto, S. (eds) Rough Set Theory and Granular Computing. Studies in Fuzziness and Soft Computing, vol 125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36473-3_1
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DOI: https://doi.org/10.1007/978-3-540-36473-3_1
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