You work in the machine learning department of a major retail company. Your team is working on a model to predict the region with the highest sales for a given quarter. You have selected your observations from past sales cycles for all regions and split your data into training and evaluation datasets. You are now training your linear learner model in Amazon SageMaker. You are trying to select the model hyperparameters that give your team the best predictions.
You have set the predictor_type hyperparameter to binary_classifier. Which loss function hyperparameter setting is NOT one of your options?

Answer options:

A.auto
B.logistic
C.hinge_loss
D.softmax_loss

Answer: D
Option A is incorrect. The three hyperparameters values that you can set for the loss function are auto, logistic, and hinge_loss. The default for auto is logistic.
Option B is incorrect. The three hyperparameters values that you can set for the loss function are auto, logistic, and hinge_loss. The default for auto is logistic.
Option C is incorrect. The three hyperparameters values that you can set for the loss function are auto, logistic, and hinge_loss. The default for auto is logistic.
Option D is correct. The three hyperparameters values that you can set for the loss function are auto, logistic, and hinge_loss. The default for auto is logistic. The softmax_loss setting is an option if your predictor_type is set to multiclass_classifier.
Reference:
Please see the Amazon SageMaker developer guide titled Linear Learner Hyperparameters.