Train the AdaBoost classifier
Now that you've instantiated the AdaBoost classifier ada
, it's time train it. You will also predict the probabilities of obtaining the positive class in the test set. This can be done as follows:
Once the classifier ada
is trained, call the .predict_proba()
method by passing X_test
as a parameter and extract these probabilities by slicing all the values in the second column as follows:
ada.predict_proba(X_test)[:,1]
The Indian Liver dataset is processed for you and split into 80% train and 20% test. Feature matrices X_train
and X_test
, as well as the arrays of labels y_train
and y_test
are available in your workspace. In addition, we have also loaded the
instantiated model ada
from the previous exercise.
This exercise is part of the course
Machine Learning with Tree-Based Models in Python
Exercise instructions
Fit
ada
to the training set.Evaluate the probabilities of obtaining the positive class in the test set.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Fit ada to the training set
____
# Compute the probabilities of obtaining the positive class
y_pred_proba = ____.____(____)[____]