Classification

The data classification process: a) Learning: Training data are analyzed by a classification algorithm. b) Classification: Test data are used to estimate the accuracy of the classification rules. If the accuracy is considered acceptable, the rules can be applied to the classification of new data tuples.

Classification have more than one algorithms include: Classification by back propagation, Decision tree(Decision tree induction and tree pruning), Bayesian classification(Naive Bayesian classification and Bayesian belief networks), Classification using association rules and Other classification methods(k-nearest neighbor classifiers, Genetic algorithms and Rough set theory.