'Predict class log-probabilities for X.
The predicted class log-probabilities of an input sample is computed as
the weighted mean predicted class log-probabilities of the classifiers
in the ensemble.
Parameters
X : {array-like, sparse matrix} of shape = [n_samples, n_features]
The training input samples. Sparse matrix can be CSC, CSR, COO,
DOK, or LIL. DOK and LIL are converted to CSR.
Returns
p : array of shape = [n_samples]
The class probabilities of the input samples. The order of
outputs is the same of that of the `classes_` attribute.'

def predict_log_proba(self, X):

    return np.log(self.predict_proba(X))
