This study explores a relationship between task characteristics and the performance of inductive learning models. The paper investigating an internal structure of domain tasks as represented by attributes and their respective values as well as typical inductive learning algorithms. A potential mapping between a problem space and a solution space is predicted to enhance the predictive accuracy of human decision-making models