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Predicting whether a new customer will churn

As you saw in the video, to train a model using sklearn:

from sklearn.svm import SVC
  • Instantiate it:
svc = SVC()
  • Train it, or "fit it", to the data:
svc.fit(telco['data'], telco['target'])

Here, the first argument consists of the features, while the second argument is the label that we are trying to predict - whether or not the customer will churn. After you've fitted the model, you can use the model's .predict() method to predict the label of a new customer.

This process is true no matter which model you use, and sklearn has many! In this exercise, you'll use LogisticRegression.

This exercise is part of the course

Marketing Analytics: Predicting Customer Churn in Python

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import LogisticRegression
Edit and Run Code