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.
Cet exercice fait partie du cours
Building Recommendation Engines with PySpark
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]
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Complete the lists below
ranks = [____, ____, ____, ____]
maxIters = [____, ____, ____, ____]
regParams = [____, ____, ____]
alphas = [____, ____, ____, ____]