1. Load the data file
Create a data-frame with three columns (1) Goal; (2) num_donors and (3) funding_status
Convert values in column funding_status from text to integers (completed=1; NotCompleted=0);
and perform 70:30 (i.e., 70% training data and remaining test data) split and create two data-frames: (1) train and (2) test. The rows must be selected randomly (2 points)
2. Use train data-frame to train a decision tree model (2 points).
3. Plot the tree (2 points).
4. Use test data-frame to show confusion matrix and model accuracy (2 points).
5. Perform steps 1-4 with two columns: (1) Goal and (2) funding_status, and document the change in accuracy as a comment (2 points).
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