This paper focuses on the application of rough set constructs to inductive learning from a database. A design guideline is suggested, which provides users the option to choose app...
Most data-mining techniques seek a single model that optimizes an objective function with respect to the data. In many real-world applications several models will equally optimize...
Various algorithms can compute approximate feasible points or approximate solutions to equality and bound constrained optimization problems. In exhaustive search algorithms for gl...
This paper deals with test case selection from axiomatic specifications whose axioms are quantifier-free first-order formulae. Test cases are modeled as ground formulae and any spe...
The Bayes factor is a useful tool for evaluating sets of inequality and about equality constrained models. In the approach described, the Bayes factor for a constrained model with...