:py:mod:`sklearn_pmml_model.base`
=================================

.. py:module:: sklearn_pmml_model.base


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

Classes
~~~~~~~

.. autoapisummary::

   sklearn_pmml_model.base.PMMLBaseEstimator
   sklearn_pmml_model.base.PMMLBaseClassifier
   sklearn_pmml_model.base.PMMLBaseRegressor
   sklearn_pmml_model.base.OneHotEncodingMixin
   sklearn_pmml_model.base.IntegerEncodingMixin



Functions
~~~~~~~~~

.. autoapisummary::

   sklearn_pmml_model.base.get_type
   sklearn_pmml_model.base.findall
   sklearn_pmml_model.base.parse_array
   sklearn_pmml_model.base.parse_sparse_array



Attributes
~~~~~~~~~~

.. autoapisummary::

   sklearn_pmml_model.base.array_regex


.. py:data:: array_regex

   

.. py:class:: PMMLBaseEstimator(pmml)


   Bases: :py:obj:`sklearn.base.BaseEstimator`

   
   Base class for estimators, saving basic information on DataFields.


   :Parameters:

       **pmml** : str, object
           Filename or file object containing PMML data.














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   .. py:method:: field_mapping()

      
      Map field name to a column index and lambda function that converts a value to the proper type.



      :Returns:

          { str: (int, callable) }
              Dictionary mapping column names to tuples with 1) index of the column
              and 2) type of the column.













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   .. py:method:: _get_param_names()
      :classmethod:

      
      Get parameter names for the estimator
















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   .. py:method:: fields()

      
      Return an ordered mapping from field name to XML DataField or DerivedField element.



      :Returns:

          OrderedDict { str: eTree.Element }
              Where keys indicate field names, and values are XML elements.













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   .. py:method:: target_field()

      
      Return the XML DataField or DerivedField element corresponding to the classification target.



      :Returns:

          eTree.Element
              Representing the target field for classification, or None if no
              MiningSchema or MiningField specified.













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   .. py:method:: fit(x, y)

      
      Not supported: PMML models are already fitted.
















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   .. py:method:: _prepare_data(X)


   .. py:method:: predict(X, *args, **kwargs)

      
      Predict class or regression value for X.

      This call is preceded with a data preprocessing step, that enables data scaling
      and categorical feature encoding.

      For more information on parameters, check out the specific implementation in the
      scikit-learn subclass.















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   .. py:method:: predict_proba(X, *args, **kwargs)

      
      Predict class probabilities for X.

      This call is preceded with a data preprocessing step, that enables data scaling
      and categorical feature encoding.

      For more information on parameters, check out the specific implementation in the
      scikit-learn subclass.















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.. py:function:: get_type(data_field, derives=None)

   
   Parse type defined in <DataField> object and returns it.


   :Parameters:

       **data_field** : eTree.Element
           <DataField> or <DerivedField> XML element that describes a column.

       **derives** : eTree.Element
           <DataField> XML element that the derived field derives.

   :Returns:

       callable
           Type of the value, as a callable function.













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.. py:class:: PMMLBaseClassifier(pmml)


   Bases: :py:obj:`PMMLBaseEstimator`

   
   Base class for classifiers, preparing classes, target fields.


   :Parameters:

       **pmml** : str, object
           Filename or file object containing PMML data.














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.. py:class:: PMMLBaseRegressor(pmml)


   Bases: :py:obj:`PMMLBaseEstimator`

   
   Base class for regressors.


   :Parameters:

       **pmml** : str, object
           Filename or file object containing PMML data.














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.. py:function:: findall(element, path)

   
   Safe helper method to find XML elements with guaranteed return type.
















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.. py:function:: parse_array(array)

   
   Convert <Array> or <SparseArray> element into list.


   :Parameters:

       **array** : eTree.Element (Array or SparseArray)
           PMML <Array> or <SparseArray> element, or type-prefixed variant (e.g., <REAL-Array>).

   :Returns:

       **output** : list
           Python list containing the items described in the PMML array element.













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.. py:function:: parse_sparse_array(array)

   
   Convert <SparseArray> element into list.


   :Parameters:

       **array** : eTree.Element (SparseArray)
           PMML <SparseArray> element, or type-prefixed variant (e.g., <REAL-SparseArray>).

   :Returns:

       **output** : list
           Python list containing the items described in the PMML sparse array element.













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.. py:class:: OneHotEncodingMixin


   
   Mixin class to automatically one-hot encode categorical variables.
















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   .. py:method:: _prepare_data(X)



.. py:class:: IntegerEncodingMixin


   
   Mixin class to automatically integer encode categorical variables.
















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   .. py:method:: _prepare_data(X)