What Is Grid search?

Grid search is a hyperparameter optimization technique used to find the best combination of hyperparameters for a machine learning model or trading algorithm. Grid search involves exhaustively searching through a manually specified subset of the hyperparameter space and evaluating each combination using a performance metric, such as accuracy or Sharpe ratio.

Although grid search can be computationally expensive, it is often used when the search space is relatively small or when a more thorough exploration of the hyperparameter space is desired. Other optimization techniques, such as random search or Bayesian optimization, can be more efficient in cases where the search space is large or the performance landscape is complex.

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