| 摘要 |
<P>PROBLEM TO BE SOLVED: To provide a risk prediction device and method for identifying an attribute highly related to a target risk factor by using unbalanced training data in which the number of instances of large classes is much larger than that of small classes and accurately predicting a risk of an event. Ž<P>SOLUTION: The risk prediction device receives an evaluation parameter which includes a wrong classification cost of instances from large classes and small classes, and a sensitivity threshold of the small classes, represents costs of respective wrong classifications when the costs of the wrong classifications are known, and represents the sensitivity threshold of the small classes when the costs are unknown. The risk prediction device returns a superior score of the attribute subset for a classification of unbalanced data by generating a candidate attribute subset, calculating the total costs of the instance wrong classifications and calculating a score that represents how excellent a selected attribute for an instance classification according to a scoring procedure based on the evaluation parameter, and performs the risk prediction on the basis of the attribute subset selected with the superior score. Ž<P>COPYRIGHT: (C)2010,JPO&INPIT Ž
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