Section 1: Data preparation You will need to separate the original data set to training and testing data for classification experiments. Describe what examples in your training and what in your test data. Section 2: Build and tune decision tree models First build a DT model using the default setting, and then tune the parameters to see if better model can be generated. Compare these models using appropriate evaluation measures. Describe and compare the patterns learned in these models. Section 3: Prediction After building the classication model, apply it to the disputed papers to nd out the authorship and report the performance accuracy of your models