Computer Vision and Image Processing
Random search is an optimization technique used to find the best parameters for a model by randomly sampling from a predefined set of values. This method is particularly useful in supervised learning when the parameter space is large and the computational cost of evaluating each combination is high. By exploring random combinations, it can often identify good solutions more efficiently than exhaustive search methods.
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