human
Solve the following python programming problem given the following code:
def all_estimators(include_meta_estimators = False, include_other = False, type_filter = None, include_dont_test = False) : 
    'Get a list of all estimators from sklearn.

    This function crawls the module and gets all classes that inherit
    from BaseEstimator. Classes that are defined in test-modules are not
    included.
    By default meta_estimators such as GridSearchCV are also not included.

    Parameters
    ----------
    include_meta_estimators : boolean, default=False
        Whether to include meta-estimators that can be constructed using
        an estimator as their first argument. These are currently
        BaseEnsemble, OneVsOneClassifier, OutputCodeClassifier,
        OneVsRestClassifier, RFE, RFECV.

    include_other : boolean, default=False
        Wether to include meta-estimators that are somehow special and can
        not be default-constructed sensibly. These are currently
        Pipeline, FeatureUnion and GridSearchCV

    include_dont_test : boolean, default=False
        Whether to include "special" label estimator or test processors.

    type_filter : string, list of string,  or None, default=None
        Which kind of estimators should be returned. If None, no filter is
        applied and all estimators are returned.  Possible values are
        \'classifier\', \'regressor\', \'cluster\' and \'transformer\' to get
        estimators only of these specific types, or a list of these to
        get the estimators that fit at least one of the types.

    Returns
    -------
    estimators : list of tuples
        List of (name, class), where ``name`` is the class name as string
        and ``class`` is the actuall type of the class.
    ' 
    def is_abstract(c) : 
        if (not hasattr (c, '__abstractmethods__')) : 
            return False 
if (not len (c.__abstractmethods__)) : 
            return False 
return True 
all_classes = [] 
    path = sklearn.__path__ 
    for (importer, modname, ispkg) in pkgutil.walk_packages (path = path, prefix = 'sklearn.', onerror =...

    
    

    Fix the buggy line: estimators = [c for c in all_classes if (issubclass (name [1], BaseEstimator) and (c [0] != 'BaseEstimator'))]
assistant
#Here is Python code to fix the buggy line: estimators = [c for c in all_classes if (issubclass (name [1], BaseEstimator) and (c [0] != 'BaseEstimator'))]
.

estimators = [c for c in all_classes if (issubclass (c [1], BaseEstimator) and (c [0] != 'BaseEstimator'))]