We will go back to the original Supervised Learning Challenges.
For the house representatives data set, calculate the accuracy, precision, recall and f1 scores of each classifier you built (on the test set).
For each, draw the ROC curve and calculate the AUC.
Calculate the same metrics you did in challenge 1, but this time in a cross validation scheme with the cross_val_score function (like in Challenge 9)
For your movie classifiers, calculate the precision and recall for each class.
Draw the ROC curve (and calculate AUC) for the logistic regression classifier from challenge 12