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Explain how hyperparameter tuning is automated in AutoML. Discuss the methods used for hyperparameter optimization and how they impact the performance and efficiency of the model training process.
A
Grid search, random search, and Bayesian optimization.
B
Genetic algorithms, simulated annealing, and particle swarm optimization.
C
Gradient descent, Newton's method, and conjugate gradient.
D
Linear programming, dynamic programming, and branch and bound.
