Module 9 - Practice - Decision Trees
Exercise 1:
Using the diabetes.csv file from the Module 8 Exercises notebook, load the file as a dataframe. Repeat the steps from exercises 1 & 2 in the Module 8 Exercise notebook to prepare your dataset for modeling.
Exercise 2:
Using the decision tree function in the scikit-learn library (sklearn), fit the model with the training dataset. Then score the model for training; how well did it do?
Exercise 3:
Now use the test dataset on the decision tree function and get its score.
Exercise 4:
Make a confusion matrix for the predicted outcomes to compare it against the "true" outcomes. How many values for each outcome did the model get incorrect?
Exercise 5:
Get a classification report on the model for the predicted data. Which outcome is the model more accurate at predicting?
Exercise 6:
Compare the predictions from the decision tree model to the logistic regression model in the Module 8 Exercise notebook. Which model was best at predicting the outcome of diabetes for a patient?