Patent ID: 8370276

Claim:
A rule learning method, which makes a computer execute a rule learning processing in machine learning, the method comprising: calculating weights of features, registered in a training example data storage unit storing a plurality of training examples correlated with one or a plurality of the features, based on a weight of each training example correlated with each of the features; sorting the features in descending order of the weights of the features; distributing the features to a given number of buckets in the descending order; specifying a maximum gain value feature in a bucket as a specified rule, where a gain of each feature in the bucket is calculated based on the weight of each training example which includes that feature; calculating a confidence value of the specified rule based on the weight of a correlated training example; storing a combination of the specified rule and the confidence value in a rule data storage unit; updating weights of the training examples based on the specified rule, the confidence value of the specified rule, data of the training examples, and the weights of the training examples; and repeating the distributing, the specifying, the calculating, the storing, and the updating, when the rule and the confidence value are to be further generated after the updating is applied to all the buckets.