from sklearn.decomposition import PCA
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.ensemble import ExtraTreesClassifier
from sklearn.mixture import GaussianMixture

clf = Pipeline([
    ('scaler', StandardScaler()),
    ('pca', PCA()),
    ('gmm', GaussianMixture()),
    ('model', ExtraTreesClassifier())
])

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-16-9adcdd00f09c> in <module>()
      3     ('pca', PCA()),
      4     ('gmm', GaussianMixture()),
----> 5     ('model', ExtraTreesClassifier())
      6 ])

/Users/samuelainsworth/research/res-venv/lib/python2.7/site-packages/sklearn/pipeline.pyc in __init__(self, steps)
    151         # shallow copy of steps
    152         self.steps = tosequence(steps)
--> 153         self._validate_steps()
    154 
    155     def get_params(self, deep=True):

/Users/samuelainsworth/research/res-venv/lib/python2.7/site-packages/sklearn/pipeline.pyc in _validate_steps(self)
    198                 raise TypeError("All intermediate steps should be "
    199                                 "transformers and implement fit and transform."
--> 200                                 " '%s' (type %s) doesn't" % (t, type(t)))
    201 
    202         # We allow last estimator to be None as an identity transformation

TypeError: All intermediate steps should be transformers and implement fit and transform. 'GaussianMixture(covariance_type='full', init_params='kmeans', max_iter=100,
        means_init=None, n_components=1, n_init=1, precisions_init=None,
        random_state=None, reg_covar=1e-06, tol=0.001, verbose=0,
        verbose_interval=10, warm_start=False, weights_init=None)' (type <class 'sklearn.mixture.gaussian_mixture.GaussianMixture'>) doesn't