Hi, As far as I understand GridSearchCV selects the parameter value with lower score but in case of multiple parameter values having the same minimum score - which is not infrequent in the case of small datasets - it always selects deterministically the first one of the group. This is usually the one with lowest value among equivalents because we usually feed ordered parameter grids to GridSearchCV. Isn't this a biased way of doing the selection? What about picking one at random (among equivalents) each time in order avoid bias through stochasticity? The related code is here: https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/grid_search.py#L352 Best, Emanuele
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