Discovering probabilistic decision rules

Techniques to generate probabilistic decision rules are presented. These techniques are used to forecast or measure the competitiveness of companies. Rules estimating the competitiveness of companies are discovered. The generated rules are then applied to forecast the competitiveness of previously unseen companies. Experimental results show that probabilistic decision rule technique outperforms many other machine learning and statistical techniques in this application domain. These ndings are further con rmed in a second application, the classi cation of credits into either good or bad credits.