40 Algorithms Every Programmer Should Know

Using the decision tree classification algorithm for the classifiers challenge

Now, let's use the decision tree classification algorithm for the common problem that we previously defined to predict whether a customer ends up purchasing a product:

1. To do, first, let's instantiate the decision tree classification algorithm and train a model using the training portion of the data that we prepared for our classifiers:

classifier = sklearn.tree.DecisionTreeClassifier(criterion = 'entropy', random_state = 100, max_depth=2)classifier.fit(X_train, y_train)

2. Now, let's use our trained model to predict the labels for the testing portion of our labeled data. Let's generate a confusion matrix that can summarize the performance of our trained model: ...