Get startedGet started for free

Binary model performance

You've already built several ALS models, so we won't do that again. An implicit ALS model has already been fitted to the binary ratings of the MovieLens dataset. Let's look at the binary_test_predictions from this model to see what we can learn.

The ROEM() function has been defined for you. Feel free to run help(ROEM) in the console if you want more details on how to execute it!

This exercise is part of the course

Building Recommendation Engines with PySpark

View Course

Exercise instructions

  • Import the col function from the pyspark.sql.functions class.
  • Take a look at binary_test_predictions using the .show() method to get an understanding of what the data looks like.
  • Call ROEM() on the binary_test_predictions to evaluate the model's performance. Do you think it performed well?
  • Use .filter() to look only at user 42's predictions (col("userId") == 42). Do you notice anything?

Hands-on interactive exercise

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

# Import the col function
from ____.sql.____ import ____

# Look at the test predictions
____.____()

# Evaluate ROEM on test predictions
____(____)

# Look at user 42's test predictions
binary_test_predictions.____(col("____") == ____).show()
Edit and Run Code