You work for a retail firm that wishes to conduct a direct mail campaign to attract new customers. Your marketing manager wishes to get answers to questions that can be put into discrete categories, such as “using historical customer email campaign responses. Should this customer receive an email from our current campaign?” You decide to use the SageMaker Linear Learner algorithm to build your model. Which hyperparameter setting would you use to get the algorithm to produce discrete results?

Answer options:

A.set the objective hyperparameter to reg:logistic.
B.set the predictor_type hyperparameter to binary_classifier.
C.set the predictor_type hyperparameter to regressor.
D.set the objective hyperparameter to reg:linear.

Answer: B
Option Ais incorrect because the objective hyperparameter is set to reg:logistic when using the XGBoost algorithm (See the AWS SageMaker developer documentation: https://docs.aws.amazon.com/sagemaker/latest/dg/xgboost_hyperparameters.html).
Option B is correct because the AWS SageMaker documentation states that you set the predictor type hyperparameter to binary_classifier when using the Linear Learner algorithm for this type of discrete classification problem. (See the AWS SageMaker documentation: https://sagemaker.readthedocs.io/en/stable/linear_learner.html).
Option C is incorrect because the predictor_type hyperparameter is set to regressor when you are using the Linear Learner algorithm for answers that are quantitative, not discrete (See the AWS SageMaker documentation: https://sagemaker.readthedocs.io/en/stable/linear_learner.html).
Option D is incorrect because the objective hyperparameter is set to reg:linear when you are using the XGBoost algorithm for quantitative answers (See the AWS SageMaker developer documentation: https://docs.aws.amazon.com/sagemaker/latest/dg/xgboost_hyperparameters.html).
Reference:
Please see the AWS SageMaker developer guide titled Using Amazon SageMaker Built-in Algorithms: https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html) for a complete description of the SageMaker hyperparameter settings.