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
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])