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。