1:concept learning:version space，decision tree等；
2:rule learning：If-then rules, association rules, genetic programming等；
3. instance-based learning（k-means, knn）,clustering等；
4：numerical approaches: ANNs , SVM,computational learning等；
5: probabilistic approaches :bayesian learning等；
6：ensembling：bagging,boosting,stacking等，combining classifiers；
8: reinforcement learning。