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Predict test data

A fitted logistic model df_fitted is available. A dataframe df_testset is available containing test data for this model. A variable fields is available, containing the list ['prediction', 'label', 'endword', 'doc', 'probability']; this is used to specify which prediction fields to print.

This exercise is part of the course

Introduction to Spark SQL in Python

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Exercise instructions

  • Apply the model to the data in df_testset.
  • Print "incorrect" if prediction does not match label.

Hands-on interactive exercise

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

# Apply the model to the test data
predictions = df_fitted.____(____).select(fields)

# Print incorrect if prediction does not match label
for x in predictions.take(8):
    print()
    if x.label != int(x.____):
        print("INCORRECT ==> ")
    for y in fields:
        print(y,":", x[y])
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