グリッドサーチを使用時、ValueErrorが出るときの対処法

前提・実現したいこと

グリッドサーチを使い、ＳＧＤ(確率的勾配降下法）のモデルを動かそう
としています。
グリッドサーチの部分で以下のエラーメッセージが発生しました。
■■な機能を実装中に以下のエラーメッセージが発生しました。

発生している問題・エラーメッセージ

Fitting 5 folds for each of 18 candidates, totalling 90 fits
[Parallel(n_jobs=-1)]: Using backend LokyBackend with 2 concurrent workers.
---------------------------------------------------------------------------
_RemoteTraceback                          Traceback (most recent call last)
_RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/joblib/externals/loky/process_executor.py", line 431, in _process_worker
    r = call_item()
  File "/usr/local/lib/python3.6/dist-packages/joblib/externals/loky/process_executor.py", line 285, in __call__
    return self.fn(*self.args, **self.kwargs)
  File "/usr/local/lib/python3.6/dist-packages/joblib/_parallel_backends.py", line 593, in __call__
    return self.func(*args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/joblib/parallel.py", line 253, in __call__
    for func, args, kwargs in self.items]
  File "/usr/local/lib/python3.6/dist-packages/joblib/parallel.py", line 253, in <listcomp>
    for func, args, kwargs in self.items]
  File "/usr/local/lib/python3.6/dist-packages/sklearn/model_selection/_validation.py", line 504, in _fit_and_score
    estimator = estimator.set_params(**cloned_parameters)
  File "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/_stochastic_gradient.py", line 114, in set_params
    super().set_params(**kwargs)
  File "/usr/local/lib/python3.6/dist-packages/sklearn/base.py", line 236, in set_params
    (key, self))
ValueError: Invalid parameter maxiter for estimator SGDRegressor(alpha=0.0001, average=False, early_stopping=False, epsilon=0.1,
             eta0=0.1, fit_intercept=True, l1_ratio=0.15,
             learning_rate='invscaling', loss='squared_loss', max_iter=1000,
             n_iter_no_change=5, penalty='l2', power_t=0.25, random_state=None,
             shuffle=True, tol=0.001, validation_fraction=0.1, verbose=0,
             warm_start=False). Check the list of available parameters with `estimator.get_params().keys()`.
"""

The above exception was the direct cause of the following exception:

ValueError                                Traceback (most recent call last)
<ipython-input-64-9c4b90a758bc> in <module>()
     10 
     11 grid_search = GridSearchCV(model, param_grid, cv=5, scoring='neg_mean_squared_error', verbose=2, n_jobs=-1)
---> 12 grid_search.fit(X_train_std, y_train)

7 frames
/usr/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
    382     def __get_result(self):
    383         if self._exception:
--> 384             raise self._exception
    385         else:
    386             return self._result

ValueError: Invalid parameter maxiter for estimator SGDRegressor(alpha=0.0001, average=False, early_stopping=False, epsilon=0.1,
             eta0=0.1, fit_intercept=True, l1_ratio=0.15,
             learning_rate='invscaling', loss='squared_loss', max_iter=1000,
             n_iter_no_change=5, penalty='l2', power_t=0.25, random_state=None,
             shuffle=True, tol=0.001, validation_fraction=0.1, verbose=0,
             warm_start=False). Check the list of available parameters with `estimator.get_params().keys()`.

該当のソースコード

#言語名：python3

# グリッドサーチの実行
param_grid = [
        {'maxiter':[10.,100.,1000], 'eta0': [0.1,0.01,0.001],
         'alpha': [1e-04,1e-09]
        }
    ]

model = SGDRegressor()

grid_search = GridSearchCV(model, param_grid, cv=5, scoring='neg_mean_squared_error', verbose=2, n_jobs=-1)
grid_search.fit(X_train_std, y_train)