text: # Copyright (C) 2019-2021 Ruhr West University of Applied Sciences, Bottrop, Germany
  # AND Elektronische Fahrwerksysteme GmbH, Gaimersheim Germany
  #
  # This Source Code Form is subject to the terms of the Apache License 2.0
  # If a copy of the APL2 was not distributed with this
  # file, You can obtain one at https://www.apache.org/licenses/LICENSE-2.0.txt.
  
  """
  API Reference
  =============
  This is the detailled API reference for the confidence calibration framework. This framework can be used to
  obtain well-calibrated confidence estimates from biased estimators like Neural Networks.
  The API reference contains a detailled description of all available methods and their parameters. For
  miscellaneous examples on how to use these methods, see readme below.
  
  Available packages
  
  .. autosummary::
     :toctree: _autosummary
  
     binning
     scaling
     regularization
     metrics
     presentation
  
  
  Each calibration method must inherit the base class :class:`AbstractCalibration`. If you want to write your own method and
  include into the framework, include this class as the base class.
  
  .. autosummary::
     :toctree: _autosummary_abstract_calibration
     :template: custom_class.rst
  
     AbstractCalibration
  
  """
  
  name = 'calibration'
  __version__ = '1.2.0'
  
  from .AbstractCalibration import AbstractCalibration
  from .Decorator import accepts, dimensions, global_accepts, global_dimensions
  from .Context import manual_seed, redirect
  from .Stats import hpdi
  