ml_grid.model_classes.FLAMLClassifierWrapper
============================================

.. py:module:: ml_grid.model_classes.FLAMLClassifierWrapper

.. autoapi-nested-parse::

   FLAML Classifier Wrapper.

   This module provides a scikit-learn compatible wrapper for FLAML's AutoML.



Attributes
----------

.. autoapisummary::

   ml_grid.model_classes.FLAMLClassifierWrapper.AutoML
   ml_grid.model_classes.FLAMLClassifierWrapper.logger


Classes
-------

.. autoapisummary::

   ml_grid.model_classes.FLAMLClassifierWrapper.FLAMLClassifierWrapper


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

.. py:data:: AutoML
   :value: None


.. py:data:: logger

.. py:class:: FLAMLClassifierWrapper(time_budget: int = 60, metric: str = 'auto', task: str = 'classification', n_jobs: int = -1, eval_method: str = 'auto', split_ratio: float = 0.2, n_splits: int = 5, log_file_name: str = 'flaml.log', seed: int = 42, verbose: int = 0, estimator_list: Union[str, List[str]] = 'auto')

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


   A scikit-learn compatible wrapper for FLAML AutoML.


   .. py:attribute:: time_budget
      :value: 60



   .. py:attribute:: metric
      :value: 'auto'



   .. py:attribute:: task
      :value: 'classification'



   .. py:attribute:: n_jobs
      :value: -1



   .. py:attribute:: eval_method
      :value: 'auto'



   .. py:attribute:: split_ratio
      :value: 0.2



   .. py:attribute:: n_splits
      :value: 5



   .. py:attribute:: log_file_name
      :value: 'flaml.log'



   .. py:attribute:: seed
      :value: 42



   .. py:attribute:: verbose
      :value: 0



   .. py:attribute:: estimator_list
      :value: 'auto'



   .. py:attribute:: model_
      :value: None



   .. py:method:: fit(X: Union[numpy.ndarray, pandas.DataFrame], y: Union[numpy.ndarray, pandas.Series], **kwargs) -> FLAMLClassifierWrapper


   .. py:method:: predict(X: Union[numpy.ndarray, pandas.DataFrame]) -> numpy.ndarray


   .. py:method:: predict_proba(X: Union[numpy.ndarray, pandas.DataFrame]) -> numpy.ndarray