:py:mod:`bluecast.conformal_prediction.conformal_prediction_regression`
=======================================================================

.. py:module:: bluecast.conformal_prediction.conformal_prediction_regression


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   bluecast.conformal_prediction.conformal_prediction_regression.ConformalPredictionRegressionWrapper




.. py:class:: ConformalPredictionRegressionWrapper(model: Any, nonconformity_measure_scorer: Callable = absolute_error)


   Bases: :py:obj:`bluecast.conformal_prediction.base_classes.ConformalPredictionWrapperBaseClass`

   Calibrate a model instance given a calibration set.

   :param model: An already fitted model instance of any type
   :param nonconformity_measure_scorer: A function object to calculate nonconformity scores with args
       y_calibration, preds

   .. py:method:: plot_non_conformity_scores(nonconformity_scores: List[float]) -> None

      Plot the distribution of nonconformity scores.
      :param nonconformity_scores: List of nonconformity scores


   .. py:method:: calibrate(x_calibration, y_calibration)

      Calibrate a model instance given a calibration set.

      :param x_calibration: Calibration set features. Must be unseen data for the model
      :param y_calibration: Calibration set labels or values


   .. py:method:: predict(x)


   .. py:method:: _calculate_intervals(y_hat: numpy.ndarray, quantiles: List[float], alphas: List[float]) -> pandas.DataFrame

      Add lower and upper prediction bands for every quantile in quantiles.


   .. py:method:: predict_interval(x: pandas.DataFrame, alphas: List[float]) -> pandas.DataFrame