'Use the optimized pipeline to estimate the class probabilities for a feature set.
Parameters
features: array-like {n_samples, n_features}
Feature matrix of the testing set
Returns
array-like: {n_samples, n_target}
The class probabilities of the input samples'

def predict_proba(self, features):

    if (not self.fitted_pipeline_):
        raise RuntimeError('A    pipeline    has    not    yet    been    optimized.    Please    call    fit()    first.')
    else:
        if (not hasattr(self.fitted_pipeline_, 'predict_proba')):
            raise RuntimeError('The    fitted    pipeline    does    not    have    the    predict_proba()    function.')
        return self.fitted_pipeline_.predict_proba(features.astype(np.float64))
