Fork this and do a cd src. You can run the following commands:
MyClassifier training.csv testing.csv CwhereCis in{NB, DT}for a Naive Bayes Classifier and Decision Tree classifier respectively. If you are using the classifier withDT(a decision tree), and you would like to view a textual representation of the tree, you are free to append the flag--printTreeon the end of this command. The tree will print before the testing data is classified as yes or no.MyClassifier data.txt --stratify. This breaks up the rows ofdata.txtinto 10 folds with "yes" and "no" rows evenly distributed among the folds.MyClassifier data.txt C --accuracy. Given thatdata.txtis broken up into 10 folds with the heading
fold 1
...
fold 10for each, running this command will output the accuracy of the given Classifier C on each fold, and then finally give an average overall accuracy as the last line of output.