Data used to optimize the parameter settings of a supervised learner model.
A) training
B) test
C) verification
D) validation

Question

Quizplus · Accepted Answer

The process of optimizing parameter settings of a supervised learner model is accomplished through a technique called hyperparameter tuning, which involves adjusting the parameters of the machine learning model and evaluating the performance of the model on a validation dataset. The validation dataset is used to fine-tune the model and find the best hyperparameters to produce the best results on unseen data. Therefore, the most appropriate choice for data used in hyperparameter tuning is validation data (choice D).

Data Used to Optimize the Parameter Settings of a Supervised