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from sklearn import cross_validation
from sklearn import grid_search
def cross_val_score(model, X, *args, **kwargs):
X = DataWrapper(X)
return cross_validation.cross_val_score(model, X, *args, **kwargs)
class GridSearchCV(grid_search.GridSearchCV):
def fit(self, X, *params, **kwparams):
return super(GridSearchCV, self).fit(DataWrapper(X), *params, **kwparams)
def predict(self, X, *params, **kwparams):
return super(GridSearchCV, self).predict(DataWrapper(X), *params, **kwparams)
try:
class RandomizedSearchCV(grid_search.RandomizedSearchCV):
def fit(self, X, *params, **kwparams):
return super(RandomizedSearchCV, self).fit(DataWrapper(X), *params, **kwparams)
def predict(self, X, *params, **kwparams):
return super(RandomizedSearchCV, self).predict(DataWrapper(X), *params, **kwparams)
except AttributeError:
pass
class DataWrapper(object):
def __init__(self, df):
self.df = df
def __len__(self):
return len(self.df)
def __getitem__(self, key):
return self.df.iloc[key]
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