On Wed, 23 Nov 2016 at 19:05 Roman Yurchak <rth.yurc...@gmail.com> wrote:
> 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?
>
Actually now that I think of it, I don't know if it will be necessarily
simpler. What if I have a massive grid and only few exceptions? Enumerating
the complement of that small subset would be much more expensive than
specifying the exceptions.
What do you think?
>
> 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
> >
> >
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