Logic Regression is a new adaptive regression methodology that attempts to construct predictors as Boolean combinations of (binary) covariates. In this paper we use this algorithm to deal with single-nucleotide polymorphism (SNP) sequence data. The predictors that are found are interpretable as risk factors of the disease. Significance of these risk factors is assessed using techniques like cro...

Regression testing is an immensely important process in the maintenance phase. The prioritization of test case becomes all the more important owing to the fact that it is not feasible to run all the test cases after each and every change. The proposed work dwells on the power of fuzzy expert system to make decisions which are better than the normal expert systems. The technique uses concepts li...

Logic regression has been recognized as a tool that can identify and model non-additive genetic interactions using Boolean logic groups. Logic regression, TASSEL-GLM and SAS-GLM were compared for analytical precision using a previously characterized model system to identify the best genetic model explaining epistatic interaction of vernalization-sensitivity in barley. A genetic model containing...