.. _`Simulated Annealing Parameter Search`:

.. _`org.sysess.sympathy.machinelearning.sim_anneal_parsearch`:

Simulated Annealing Parameter Search
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.. image:: annealing_hyperparam.svg
   :width: 48


Uses simulated annealing to find the optimal parameters by considering a hyper cube of all possible indices to the given parameter table. Each column of the parameter table corresponds to one axis of this cube with a range corresponding to the non-masked rows of the parameter table. The radius for the annealing process assumes that all axes have unit length regardless of the number of non-masked rows. This node should be considered _experimental_ and may change in the future





Definition
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Input ports
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    **in-model**  model
        in-model

    **parameter space**  table
        param-space

    **X**  table
        X

    **Y**  table
        Y

    **cross-validation** 0 - 1,  [(table,table)]
        cross-validation


Output ports
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    **results**  table
        results

    **parameters**  table
        parameters

    **out-model**  model
        out-model




Configuration
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    **Cooling method** (cooling)
        Method for lowering temperature
    **Cooling argument** (cooling_arg)
        Argument A to cooling method. Exponential: T=A^t   Linear ignores A   Logarithmic: T=A/log(1+t)
    **Cross validation splits** (cv)
        Number of fold in the default K-Fold cross validation. Ignored when cross-validation port is given
    **iterations** (n_iter)
        Number of randomized searches done









Implementation
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.. automodule:: node_paramsearch
    :noindex:

.. class:: ParameterSearch_SimulatedAnnealing
    :noindex: