error

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-229-0c627bda0543> in <module>()
      5           }
      6 gs = GridSearchCV(clf_SVM, params, cv=5, scoring='roc_auc')
----> 7 gs.fit(corpus1, y)

/usr/local/lib/python2.7/dist-packages/sklearn/grid_search.pyc in fit(self, X, y)
    594 
    595         """
--> 596         return self._fit(X, y, ParameterGrid(self.param_grid))
    597 
    598 

/usr/local/lib/python2.7/dist-packages/sklearn/grid_search.pyc in _fit(self, X, y, parameter_iterable)
    376                                     train, test, self.verbose, parameters,
    377                                     self.fit_params, return_parameters=True)
--> 378             for parameters in parameter_iterable
    379             for train, test in cv)
    380 

/usr/local/lib/python2.7/dist-packages/sklearn/externals/joblib/parallel.pyc in __call__(self, iterable)
    651             self._iterating = True
    652             for function, args, kwargs in iterable:
--> 653                 self.dispatch(function, args, kwargs)
    654 
    655             if pre_dispatch == "all" or n_jobs == 1:

/usr/local/lib/python2.7/dist-packages/sklearn/externals/joblib/parallel.pyc in dispatch(self, func, args, kwargs)
    398         """
    399         if self._pool is None:
--> 400             job = ImmediateApply(func, args, kwargs)
    401             index = len(self._jobs)
    402             if not _verbosity_filter(index, self.verbose):

/usr/local/lib/python2.7/dist-packages/sklearn/externals/joblib/parallel.pyc in __init__(self, func, args, kwargs)
    136         # Don't delay the application, to avoid keeping the input
    137         # arguments in memory
--> 138         self.results = func(*args, **kwargs)
    139 
    140     def get(self):

/usr/local/lib/python2.7/dist-packages/sklearn/cross_validation.pyc in _fit_and_score(estimator, X, y, scorer, train, test, verbose, parameters, fit_params, return_train_score, return_parameters)
   1237         estimator.fit(X_train, **fit_params)
   1238     else:
-> 1239         estimator.fit(X_train, y_train, **fit_params)
   1240     test_score = _score(estimator, X_test, y_test, scorer)
   1241     if return_train_score:

/usr/local/lib/python2.7/dist-packages/sklearn/svm/base.pyc in fit(self, X, y)
    672         """
    673         self._enc = LabelEncoder()
--> 674         y_ind = self._enc.fit_transform(y)
    675         if len(self.classes_) < 2:
    676             raise ValueError("The number of classes has to be greater than"

/usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/label.pyc in fit_transform(self, y)
    123         y : array-like of shape [n_samples]
    124         """
--> 125         y = column_or_1d(y, warn=True)
    126         _check_numpy_unicode_bug(y)
    127         self.classes_, y = np.unique(y, return_inverse=True)

/usr/local/lib/python2.7/dist-packages/sklearn/utils/validation.pyc in column_or_1d(y, warn)
    317         return np.ravel(y)
    318 
--> 319     raise ValueError("bad input shape {0}".format(shape))
    320 
    321 

ValueError: bad input shape (1380, 4)