'Use the optimized pipeline to predict the target for a feature set.
Parameters
features: array-like {n_samples, n_features}
Feature matrix
Returns
array-like: {n_samples}
Predicted target for the samples in the feature matrix'

def predict(self, features):

    if (not self.fitted_pipeline_):
        raise RuntimeError('A    pipeline    has    not    yet    been    optimized.    Please    call    fit()    first.')
    features = features.astype(np.float64)
    if np.any(np.isnan(features)):
        features = self._impute_values(features)
    return self.fitted_pipeline_.predict(features)
