Abstract
In our research we used a microRNA expression level data set describing eleven types of human cancers. Our methodology was based on data mining (rule induction) using rough set theory. We used a novel methodology based on rule generations and cumulative rule sets. The original testing data set described only four types of cancer. We further restricted our attention to two types of cancer: breast and ovary. Using our combined rule set, all but one cases of breast cancer and all cases of ovary cancer were correctly classified.
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Fang, J., Grzymala-Busse, J.W. (2006). Mining of MicroRNA Expression Data—A Rough Set Approach. In: Wang, GY., Peters, J.F., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2006. Lecture Notes in Computer Science(), vol 4062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11795131_110
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DOI: https://doi.org/10.1007/11795131_110
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