1. WEKA : CLASSIFICATION

2. Classification ID3 J48 3. Predicted target must be categorical Implemented methods decision trees(J48, etc.) and rules Nave Bayes neural networks instance-based classifiers Evaluation methods test data set crossvalidation 4. After loaded a data file, click Classify Choose a classifier, Under Classifier: click choose, then a drop- down menu appears, Click trees and select J48 a decision tree algorithm Select a test option Select percentage split with default ratio 66% for training and 34% for testing Click Start to train and test the classifier. The training and testing information will be displayed in classifier output window. 5. Classifier () Bayers Functions Lazy Meta Misc Trees Rules 6. k-fold cross validation leave-one-out validation, test data training data 3/10, 3/10 4/10 7. Weka Explorer weather.nominal.arff filter Classify Weka Explorer Open file C:/Program Files/Weka-3- 6/data/weather.nominal.arff 8. Classify ID3 Classify Choose Classifiers Trees ID3 9. use training set Start 10. Visualize Tree 11. Preprocess Choose Weka Filters Unsupervised attribute Discretize 12. bin = 3 13. Classify J48 Classify Choose Classifiers Trees J48 14. J48 Weka Explorer Open file C:/Program Files/Weka-3-6/data/iris.arff 15. More options Output prediction