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The importance of finding the characteristics leading to either a success or a failure is one of the driving forces of data mining. The various application areas of finding success/failure factors cover vast variety of areas such as credit risk evaluation and granting loans, micro array analysis, health factors and health risk factors, and parameter combinations leading to a product success. This paper presents a new approach for making inferences about dichotomous data. The objective is to determine rules that lead to a certain result.
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