ATTRIBUTE VALUE PREDICTING METHOD AND SYSTEM IN THE LEARNING SYSTEM

Method and system of predicting attribute value in the learning system, (a) where expected value of equivalent example and its classification class is generated by domain knowledge, with respect to the test example being supplemented with candidates of a plural number of attribute values, in which the attribute lacking part of attribute values can adopt in the learning system, having (i) attribute descriptions containing a plural number of training examples, each of which contains attribute and its attribute value, and such training example and classification class adopted by each training example, and (ii) domain knowledge generating a pair of second example and its classification class from a pair of first example and its classification class, as equivalent example, (b) where classification class of equivalent example generated as above is predicted by decision tree produced based on the above attribute descriptions, and (c) where the attribute value lacking the above test example is predicted by use of the expected value of classification class and the above prediction result with respect to the above equivalent example.