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Advantages and Disadvantages of the SMBO Method

Understand how Sequential Model-Based Optimization (SMBO) balances exploration and exploitation for hyperparameter optimization. Learn its benefits in efficient resource use and automated tuning, alongside challenges like reliance on initial parameters and risk of local minima.

Advantages of the SMBO method

  • Efficient use of resources: SMBO selects the most promising set of hyperparameters to evaluate the machine learning model and then updates its internal model (probabilistic model) based on the results. This results in more efficient use of computational resources because the model is not evaluated on hyperparameters that are unlikely to produce the best result. ...