Hi!
What you could do is specify lists of dicts to group the parameters which
apply together in one dict...
[{'learning_rate': ['constant', 'invscaling', 'adaptive'], 'solver':
'sgd'}, {'solver': 'adam'}]
```py
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import GridSearchCV
from sklearn.datasets import make_classification
from pandas import DataFrame
X, y = make_classification(random_state=42)
gs = GridSearchCV(MLPClassifier(random_state=42),
param_grid=[{'learning_rate': ['constant', 'invscaling',
'adaptive'],
'solver': ['sgd',]},
{'solver': ['adam',]}])
DataFrame(gs.fit(X, y).cv_results_)
```
Would give
[image: Inline image 1]
HTH :)
On Wed, Nov 23, 2016 at 11:15 AM, Jaidev Deshpande <
deshpande.jai...@gmail.com> 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/ja
> rvis/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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>
>
--
Raghav RV
https://github.com/raghavrv
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