2011/10/28 Alexandre Gramfort <[email protected]>:
> class SingleSplit(object):
>
> def __init__(self, train_index, test_index):
> self.train_index = train_index
> self.test_index = test_index
>
> def __iter__(self):
> yield self.train_index, self.test_index
>
> is this more complicated than this?
It's just that in Andreas' case de datasets are already splitted. To
use the GridSearchCV you have to concatenate them to able to call the
fit API.
X_train, y_train = load_svmlight_file("/path/to/training/set.dat")
X_validation, y_validation = load_svmlight_file("/path/to/validation/set.dat")
params_grid = { ... }
cv = SingleSplit(np.arange(X_train.shape[0]),
np.arange(X_validation.shape[0]) + X_train.shape[0])
X_total = np.vstack((X_train, X_validation))
y_total = np.vstack((y_train, y_validation))
GridSearchCV(params_grid, cv=cv).fit(X_total, y_total)
This is a lot of complex boilerplate for the newcomer.
--
Olivier
http://twitter.com/ogrisel - http://github.com/ogrisel
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