Abstract
To identify anomalous conditions in the electric power apparatus, a variety of diagnosing methods such as the nueral networks and the decision tree have been used. In this paper, we have investigated the AdaBoost for its diagnosis accuracy. Adopting the neural networks as the weak learner, the diagnosis accuracy seems to be improved. Applying the test data to the rules obtained by the training data, however, we suspect that the classifier meets the over-fitting. We have to be cautious in case of using the high-performance classifier.
