AutoML class
============

.. class:: AutoML(self, models: str | list, vectorizer: str | sam_ml.data.preprocessing.embeddings.Embeddings_builder | None | list[str | sam_ml.data.preprocessing.embeddings.Embeddings_builder | None], scaler: str | sam_ml.data.preprocessing.scaler.Scaler | None | list[str | sam_ml.data.preprocessing.scaler.Scaler | None], selector: str | tuple[str, int] | sam_ml.data.preprocessing.feature_selection.Selector | None | list[str | tuple[str, int] | sam_ml.data.preprocessing.feature_selection.Selector | None], sampler: str | sam_ml.data.preprocessing.sampling.Sampler | sam_ml.data.preprocessing.sampling_pipeline.SamplerPipeline | None | list[str | sam_ml.data.preprocessing.sampling.Sampler | sam_ml.data.preprocessing.sampling_pipeline.SamplerPipeline | None])

Auto-ML parent class {abstract}  - parent class :class:`object`

.. list-table::
   :widths: 25 75
   :header-rows: 0

   * - Parameters
     - 
        models : str or list

            - string of model set from ``model_combs`` method
            - list of Wrapperclass models from sam_ml library

        vectorizer : str, Embeddings_builder, or None
            object or algorithm of :class:`Embeddings_builder` class which will be used for automatic string column vectorizing (None for no vectorizing)
        scaler : str, Scaler, or None
            object or algorithm of :class:`Scaler` class for scaling the data (None for no scaling)
        selector : str, Selector, or None
            object, tuple of algorithm and feature number, or algorithm of :class:`Selector` class for feature selection (None for no selecting)
        sampler : str, Sampler, SamplerPipeline, or None
            object or algorithm of :class:`Sampler` / :class:`SamplerPipeline` class for sampling the train data (None for no sampling)



   * - Attributes
     - 
         
        models : dict
            dictionary with model names as keys and model instances as values
        
       
         
        scores : dict[str, float]
            dictionary with scores for every model as dictionary
        
       

.. note::

   If a list is provided for one or multiple of the preprocessing steps, all model with preprocessing steps combination will be added as pipelines



.. raw:: html

   <h2>Methods</h2>

.. list-table::
   :widths: 25 75
   :header-rows: 1

   * - Method
     - Description
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML._AutoML__finish_sound`
     - little function to play a microwave sound
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML._AutoML__sort_dict`
     - Function to sort a dict by a given list of keys
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML.add_model`
     - Function for adding model in self.models
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML.eval_models`
     - Function to train and evaluate every model
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML.eval_models_cv`
     - Function to run a cross validation on every model
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML.find_best_model_mass_search`
     - Function to run a successive halving hyperparameter search for every model
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML.find_best_model_randomCV`
     - Function to run a random cross validation hyperparameter search for every model
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML.find_best_model_smac`
     - Function to run a Hyperparametertuning with SMAC library HyperparameterOptimizationFacade for every model [can only be used in the sam_ml version with swig]
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML.model_combs`
     - Function for mapping string to set of models
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML.output_scores_as_pd`
     - Function to output self.scores as pd.DataFrame
   
   * - :meth:`~sam_ml.models.main_auto_ml.AutoML.remove_model`
     - Function for deleting model in self.models
   




.. automethod:: sam_ml.models.main_auto_ml.AutoML._AutoML__finish_sound

.. automethod:: sam_ml.models.main_auto_ml.AutoML._AutoML__sort_dict

.. automethod:: sam_ml.models.main_auto_ml.AutoML.add_model

.. automethod:: sam_ml.models.main_auto_ml.AutoML.eval_models

.. automethod:: sam_ml.models.main_auto_ml.AutoML.eval_models_cv

.. automethod:: sam_ml.models.main_auto_ml.AutoML.find_best_model_mass_search

.. automethod:: sam_ml.models.main_auto_ml.AutoML.find_best_model_randomCV

.. automethod:: sam_ml.models.main_auto_ml.AutoML.find_best_model_smac

.. automethod:: sam_ml.models.main_auto_ml.AutoML.model_combs

.. automethod:: sam_ml.models.main_auto_ml.AutoML.output_scores_as_pd

.. automethod:: sam_ml.models.main_auto_ml.AutoML.remove_model