random_search_tuner
===========================================

.. py:module:: evalml.tuners.random_search_tuner

.. autoapi-nested-parse::

   Random Search Optimizer.



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

Classes Summary
~~~~~~~~~~~~~~~

.. autoapisummary::

   evalml.tuners.random_search_tuner.RandomSearchTuner





Contents
~~~~~~~~~~~~~~~~~~~
.. py:class:: RandomSearchTuner(pipeline_hyperparameter_ranges, with_replacement=False, replacement_max_attempts=10, random_seed=0)



   Random Search Optimizer.

   :param pipeline_hyperparameter_ranges: a set of hyperparameter ranges corresponding to a pipeline's parameters
   :type pipeline_hyperparameter_ranges: dict
   :param with_replacement: If false, only unique hyperparameters will be shown
   :type with_replacement: bool
   :param replacement_max_attempts: The maximum number of tries to get a unique
                                    set of random parameters. Only used if tuner is initalized with
                                    with_replacement=True
   :type replacement_max_attempts: int
   :param random_seed: Seed for random number generator. Defaults to 0.
   :type random_seed: int

   .. rubric:: Example

   >>> tuner = RandomSearchTuner({'My Component': {'param a': [0.0, 10.0], 'param b': ['a', 'b', 'c']}}, random_seed=42)
   >>> proposal = tuner.propose()
   ...
   >>> assert proposal.keys() == {'My Component'}
   >>> assert proposal['My Component'] == {'param a': 3.7454011884736254, 'param b': 'c'}

   Determines points using a random search approach.

   >>> for each in range(7):
   ...     print(tuner.propose())
   {'My Component': {'param a': 7.3199394181140525, 'param b': 'b'}}
   {'My Component': {'param a': 1.5601864044243654, 'param b': 'a'}}
   {'My Component': {'param a': 0.5808361216819947, 'param b': 'c'}}
   {'My Component': {'param a': 6.011150117432089, 'param b': 'c'}}
   {'My Component': {'param a': 0.2058449429580245, 'param b': 'c'}}
   {'My Component': {'param a': 8.32442640800422, 'param b': 'a'}}
   {'My Component': {'param a': 1.8182496720710064, 'param b': 'a'}}




   **Methods**

   .. autoapisummary::
      :nosignatures:

      evalml.tuners.random_search_tuner.RandomSearchTuner.add
      evalml.tuners.random_search_tuner.RandomSearchTuner.get_starting_parameters
      evalml.tuners.random_search_tuner.RandomSearchTuner.is_search_space_exhausted
      evalml.tuners.random_search_tuner.RandomSearchTuner.propose

   .. py:method:: add(self, pipeline_parameters, score)

      Not applicable to random search tuner as generated parameters are not dependent on scores of previous parameters.

      :param pipeline_parameters: A dict of the parameters used to evaluate a pipeline
      :type pipeline_parameters: dict
      :param score: The score obtained by evaluating the pipeline with the provided parameters
      :type score: float


   .. py:method:: get_starting_parameters(self, hyperparameter_ranges, random_seed=0)

      Gets the starting parameters given the pipeline hyperparameter range.

      :param hyperparameter_ranges: The custom hyperparameter ranges passed in during search. Used to determine the starting parameters.
      :type hyperparameter_ranges: dict
      :param random_seed: The random seed to use. Defaults to 0.
      :type random_seed: int

      :returns: The starting parameters, randomly chosen, to initialize a pipeline with.
      :rtype: dict


   .. py:method:: is_search_space_exhausted(self)

      Checks if it is possible to generate a set of valid parameters. Stores generated parameters in ``self.curr_params`` to be returned by ``propose()``.

      :returns: If no more valid parameters exists in the search space, return False.
      :rtype: bool

      :raises NoParamsException: If a search space is exhausted, then this exception is thrown.


   .. py:method:: propose(self)

      Generate a unique set of parameters.

      If tuner was initialized with ``with_replacement=True`` and the tuner is unable to
      generate a unique set of parameters after ``replacement_max_attempts`` tries, then ``NoParamsException`` is raised.

      :returns: Proposed pipeline parameters
      :rtype: dict