kernelshap_tabular
==================

.. py:module:: kernelshap_tabular


Classes
-------

.. autoapisummary::

   kernelshap_tabular.KERNELSHAPTabular


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

.. py:class:: KERNELSHAPTabular(training_data: numpy.array, mode: str = 'classification', feature_names: List[int] = None, training_data_kmeans: Optional[int] = None, silent: bool = False)

   Wrapper around the SHAP Kernel explainer for tabular data.


   .. py:attribute:: feature_names


   .. py:attribute:: mode


   .. py:attribute:: explainer
      :type:  shap.KernelExplainer


   .. py:attribute:: silent


   .. py:method:: explain(model_or_function: Union[str, callable], input_tabular: numpy.array, link: str = 'identity', **kwargs) -> numpy.array

      Run the KernelSHAP explainer.

      :param model_or_function: The function that runs the model to be explained
                                or the path to a ONNX model on disk.
      :type model_or_function: callable or str
      :param input_tabular: Data to be explained.
      :type input_tabular: np.ndarray
      :param link: A generalized linear model link to connect the feature importance values
                   to the model. Must be either "identity" or "logit".
      :type link: str
      :param kwargs: These parameters are passed on

      Other keyword arguments: see the documentation for KernelExplainer:
      https://github.com/shap/shap/blob/master/shap/explainers/_kernel.py

      :returns: An array (np.ndarray) containing the KernelExplainer explanations for each class.