Hi Jaidev, well, `param_grid` in GridSearchCV can also be a list of dictionaries, so you could directly specify the cases you are interested in (instead of the full grid - exceptions), which might be simpler?
On 23/11/16 11:15, Jaidev Deshpande wrote: > Hi, > > Sometimes when using GridSearchCV, I realize that in the grid there are > certain combinations of hyperparameters that are either incompatible or > redundant. For example, when using an MLP, if I specify the following grid: > > grid = {'solver': ['sgd', 'adam'], 'learning_rate': ['constant', > 'invscaling', 'adaptive']} > > then it yields the following ParameterGrid: > > [{'learning_rate': 'constant', 'solver': 'sgd'}, > {'learning_rate': 'constant', 'solver': 'adam'}, > {'learning_rate': 'invscaling', 'solver': 'sgd'}, > {'learning_rate': 'invscaling', 'solver': 'adam'}, > {'learning_rate': 'adaptive', 'solver': 'sgd'}, > {'learning_rate': 'adaptive', 'solver': 'adam'}] > > Now, three of these are redundant, since learning_rate is used only for > the sgd solver. Ideally I'd like to specify these cases upfront, and for > that I have a simple hack > (https://github.com/jaidevd/jarvis/blob/master/jarvis/cross_validation.py#L38). > Using that yields a ParameterGrid as follows: > > [{'learning_rate': 'constant', 'solver': 'adam'}, > {'learning_rate': 'invscaling', 'solver': 'adam'}, > {'learning_rate': 'adaptive', 'solver': 'adam'}] > > which is then simply removed from the original ParameterGrid. > > I wonder if there's a simpler way of doing this. Would it help if we had > an additional parameter (something like "grid_exceptions") in > GridSearchCV, which would remove these dicts from the list of parameters? > > Thanks > > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn