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How to get started

Fork this and do a cd src. You can run the following commands:

  1. MyClassifier training.csv testing.csv C where C is in {NB, DT} for a Naive Bayes Classifier and Decision Tree classifier respectively. If you are using the classifier with DT (a decision tree), and you would like to view a textual representation of the tree, you are free to append the flag --printTree on the end of this command. The tree will print before the testing data is classified as yes or no.
  2. MyClassifier data.txt --stratify. This breaks up the rows of data.txt into 10 folds with "yes" and "no" rows evenly distributed among the folds.
  3. MyClassifier data.txt C --accuracy. Given that data.txt is broken up into 10 folds with the heading
fold 1
...
fold 10

for 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.