Question

You are planning to use Spark to create a machine learning model that recommends restaurants to users based on user details and past ratings for restaurants What is the simplest way to implement this model? Use a Logistic Regression algorithm to train a classifier. Use a K-Means algorithm to create clusters. Use an alternating least squares (ALS) algorithm to create a collaborative filtering solution. Use a Decision Trees algorithm to train a regression model.

Answer 1

The third point i.e " Use an alternating least squares (ALS) algorithm to create a collaborative filtering solution" is the correct answer .

Step-by-step explanation:

The Alternating Less Squares is the different approach that main objective to enhancing the loss function.The Alternating Less Squares process divided the matrix into the two factors for optimizing the loss .The divided of two factor matrix is known as item matrix or the user matrix.

• As we have to build the machine learning model which proposes restaurants to restaurants that are based on the customer information and the prior restaurant reviews the alternating least squares is the best model to implement this .
• All the other options are not the correct model also they are not related to given scenario that's why they are incorrect options.