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Train the classifier

The dataframe df_trainset you created in the previous exercise is available. You're now going to use it to train a Logistic Regression Classifier.

This exercise is part of the course

Introduction to Spark SQL in Python

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Exercise instructions

  • Import the Logistic Regression Classifier.
  • Instantiate the classifier. Set maximum iterations to 100, the regularization parameter to 0.4, and the elastic net parameter to 0.0.
  • Train the classifier on the trainset.
  • Print the number of training iterations.

Hands-on interactive exercise

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

# Import the logistic regression classifier
from ____ import ____

# Instantiate logistic setting elasticnet to 0.0
logistic = ____(maxIter=100, regParam=0.4, ____=0.0)

# Train the logistic classifer on the trainset
df_fitted = ____.____(____)

# Print the number of training iterations
print("Training iterations: ", df_fitted.____.____)
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