def predict_proba(self, X):
check_rdd(X, (sp.spmatrix, np.ndarray))<EOL>return X.map(<EOL>lambda X: super(SparkBaseNB, self).predict_proba(X))<EOL>
Return probability estimates for the RDD containing test vector X.

Parameters
----------
X : RDD containing array-like items, shape = [m_samples, n_features]

Returns
-------
C : RDD with array-like items , shape = [n_samples, n_classes]
    Returns the probability of the samples for each class in
    the models for each RDD block. The columns correspond to the classes
    in sorted order, as they appear in the attribute `classes_`.