Priciple and Algorithm of Incremental Bayes Classification

Automatic classification is an important research field in data mining and machine learning.An incremental Bayes classification priciple,parameter calculation and algorithm based on small training is presented to solve the difficult problem involving getting labeled training documents.The algorithm can process two cases: the labled and unlabeled incremental documents.The labeled documents are labeled first by using the original classification,if match then remain the classifier,else the new classification is trained from the incremental documents.The unlabeled documents are labeled first by using the original classification,and then the new classification is trained from the incremental documents.The experimental results showed that this algorithm was feasible and effective with more accuracy than Naive Bayes classification algorithm.The incremental Bayes classification algorithm provides a new method for updating of classification.