ml_grid.util.validate_parameters
================================

.. py:module:: ml_grid.util.validate_parameters

.. autoapi-nested-parse::

   Functions to validate model-specific hyperparameters before grid search.



Functions
---------

.. autoapisummary::

   ml_grid.util.validate_parameters.validate_knn_parameters
   ml_grid.util.validate_parameters.validate_XGB_parameters
   ml_grid.util.validate_parameters.validate_parameters_helper


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

.. py:function:: validate_knn_parameters(parameters: Dict[str, Any], ml_grid_object: Any) -> Dict[str, Any]

   Validates the `n_neighbors` parameter for KNN classifiers.

   This function ensures that the values for `n_neighbors` do not exceed the
   number of samples in the training data. If a value is too large, it is
   capped at `n_samples - 1`.

   :param parameters: The dictionary of parameters to validate.
   :type parameters: Dict[str, Any]
   :param ml_grid_object: The main pipeline object containing the training
                          data (`X_train`).
   :type ml_grid_object: Any

   :returns: The validated parameters dictionary.
   :rtype: Dict[str, Any]


.. py:function:: validate_XGB_parameters(parameters: Dict[str, Any], ml_grid_object: Any) -> Dict[str, Any]

   Validates the `max_bin` parameter for XGBoost.

   This function checks that the max_bin values are greater than or equal to 2,
   and if not, it sets them to 2.

   :param parameters: The dictionary of parameters to validate.
   :type parameters: Dict[str, Any]
   :param ml_grid_object: The main pipeline object (currently unused).
   :type ml_grid_object: Any

   :returns: The validated parameters dictionary.
   :rtype: Dict[str, Any]


.. py:function:: validate_parameters_helper(algorithm_implementation: Any, parameters: Dict[str, Any], ml_grid_object: Any) -> Dict[str, Any]

   Dispatches to the correct parameter validation function based on algorithm type.

   :param algorithm_implementation: The scikit-learn estimator instance.
   :type algorithm_implementation: Any
   :param parameters: The dictionary of parameters to validate.
   :type parameters: Dict[str, Any]
   :param ml_grid_object: The main pipeline object containing training data.
   :type ml_grid_object: Any

   :returns: The validated parameters dictionary.
   :rtype: Dict[str, Any]