Hi, I noticed that GridSearchCV fits a new estimator from scratch for each grid point. But when working with pipelines where multiple steps have tuning parameters, some time could be saved by fitting an early step once and then fitting the later steps along a sequence of grid points while using the precomputed early step. This seems to make sense particularly with compute-intensive feature selection algorithms. However, it appears to me that this optimization would add a lot of complexity. Any thoughts?
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