def __init__(self,
estimator,
param_grid,
sc=None,
partitions='auto',
preds=False,
scoring=None,
n_jobs=None,
iid='warn',
refit=True,
cv=5,
verbose=0,
pre_dispatch='2*n_jobs',
error_score='raise-deprecating',
return_train_score=False):
GridSearchCV.__init__(self,
estimator,
param_grid,
scoring=scoring,
n_jobs=n_jobs,
iid=iid,
refit=refit,
cv=cv,
verbose=verbose,
pre_dispatch=pre_dispatch,
error_score=error_score,
return_train_score=return_train_score)
self.sc = sc
self.partitions = partitions
self.preds = preds
def __init__(self, gs_params):
"""
Args:
gs_params (dict) search parameters for hyperparameter optimization.
"""
# constructs pipline steps
scale = StandardScaler()
regressor = RandomForestRegressor()
pipe = Pipeline(steps=[('scale', scale), ('regressor', regressor)])
# constructs the gridsearch estimator
GridSearchCV.__init__(pipe, gs_params, refit=True, cv=5, scoring='r2')
