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Homework 1 (due 1/24 at 11:5pm)

As homework, you will complete and submit the in-class exercises from lecture.

Please copy each line of the grading rubric (including number) into a markdown element in your jupyter notebook that matches the cell that completes it, so we don't miss anything during grading :-)

GRADING RUBRIC for Homework 1:

1. Load csv correctly into a DataFrame and show contents in a cell	5 points
2. Dataframe is correctly split into train and holdout	5 points
3. Dataframe is correctly sliced into features and a classification target	5 points
4. A decision tree (single tree) model is correctly instantiated and trained on the features	5 points
5. The trained model is correctly used to make predictions on the holdout features	5 points
6. The accuracy score is correctly calculated on the holdout dataset	5 points
7. In another cell(s), code is correctly modified to retrain and test on a different classification target	5 points
8. Correct explanation of most important feature for decision tree in general	5 points
9. Discussion of most important feature for your trained decision tree on this dataset for first target (one paragraph)	5 points
10. Discussion of most important feature for your trained decision tree on this dataset for second target (one paragraph)	5 points

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