Match each hyperparameter tuning strategy to its description.
Drag a concept onto its matching description — or click a concept then click the description.
Exhaustive search over specified hyperparameter values
Random sampling of hyperparameter combinations
Probabilistic model to guide search
Early stopping and resource allocation
SageMaker automatic tuning
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Grid Search: Exhaustively tries all combinations of specified hyperparameter values.
The correct matches are: Grid Search exhaustively searches all combinations; Random Search samples randomly; Bayesian Optimization uses a probabilistic model. Common confusions involve swapping the descriptions of Grid Search and Random Search, or confusing Random Search with Bayesian Optimization.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Grid Search: Exhaustively tries all combinations of specified hyperparameter values.
Why this is correct
Grid Search is correctly defined as exhaustive search over all combinations.
Grid Search: Randomly samples hyperparameter combinations from a specified distribution.
Why it's wrong here
Incorrect — Grid Search does not use random sampling; that describes Random Search.
Random Search: Randomly samples hyperparameter combinations from a specified distribution.
Why this is correct
Correct — Random Search indeed samples randomly from defined distributions.
Random Search: Uses a probabilistic model to guide the search towards promising hyperparameters.
Why it's wrong here
Incorrect — Random Search does not use a probabilistic model; that describes Bayesian Optimization.
Bayesian Optimization: Uses a probabilistic model to guide the search towards promising hyperparameters.
Why this is correct
Correct — Bayesian Optimization uses a probabilistic model such as Gaussian Processes.
Go deeper
About these practice questions
Courseiva writes every MLS-C01 question from scratch — 1,672 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.