کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
518826 | 867617 | 2007 | 18 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Applying hybrid reasoning to mine for associative features in biological data Applying hybrid reasoning to mine for associative features in biological data](/preview/png/518826.png)
We develop the means to mine for associative features in biological data. The hybrid reasoning schema for deterministic machine learning and its implementation via logic programming is presented. The methodology of mining for correlation between features is illustrated by the prediction tasks for protein secondary structure and phylogenetic profiles. The suggested methodology leads to a clearer approach to hierarchical classification of proteins and a novel way to represent evolutionary relationships. Comparative analysis of Jasmine and other statistical and deterministic systems (including Explanation-Based Learning and Inductive Logic Programming) are outlined. Advantages of using deterministic versus statistical data mining approaches for high-level exploration of correlation structure are analyzed.
Journal: Journal of Biomedical Informatics - Volume 40, Issue 3, June 2007, Pages 203–220