Specify ALS hyperparameters
You're now going to build your first implicit rating recommendation engine using ALS. To do this, you will first tell Spark what values you want it to try when finding the best model.
Four empty lists are provided below. You will fill them with specific values that Spark can use to build several different ALS models. In the next exercise, you'll tell Spark to build out these models using the lists below.
This exercise is part of the course
Building Recommendation Engines with PySpark
Exercise instructions
- Fill in the following lists with the following values:
ranks = [10, 20, 30, 40]maxIters = [10, 20, 30, 40]regParams = [.05, .1, .15]alphas = [20, 40, 60, 80]
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Complete the lists below
ranks = [____, ____, ____, ____]
maxIters = [____, ____, ____, ____]
regParams = [____, ____, ____]
alphas = [____, ____, ____, ____]