|  | ## Optimize Parameters (Evolutionary)

#### Synopsis

This operator finds the optimal values for parameters using an evolutionary computation approach.

#### Description

This operator finds the optimal values for a set of parameters using an evolutionary strategies approach which is often more appropriate than a grid search or a greedy search like the quadratic programming approach and leads to better results. The parameter parameters is a list of key value pairs where the keys are of the form `operator_name.parameter_name` and the value for each parameter must be a semicolon separated pair of a minimum and a maximum value in squared parantheses, e.g. [10;100] for a range of 10 until 100. The operator returns an optimal ParameterSet which can as well be written to a file with a ParameterSetWriter. This parameter set can be read in another process using a ParameterSetLoader.

The file format of the parameter set file is straightforward and can easily be generated by external applications. Each line is of the form
`operator_name.parameter_name = value`

Please refer to section Advanced Processes/Parameter and performance analysis for an example application.

#### Input

- input 1:

#### Output

- performance:
- parameter:
- result 1:

#### Parameters

- configure operator: Configure this operator by means of a Wizard.
- parameters: The parameters.
- max generations: Stop after this many evaluations.
- use early stopping: Enables early stopping. If unchecked, always the maximum number of generations is performed.
- generations without improval: Stop criterion: Stop after n generations without improval of the performance.
- specify population size: If unchecked, one individuum per example of the delivered example set is used.
- population size: The population size.
- keep best: Indicates if the best individual should survive (elititst selection).
- mutation type: The type of the mutation operator.
- selection type: The type of the selection operator.
- tournament fraction: The fraction of the population used for tournament selection.
- crossover prob: The probability for crossover.
- use local random seed: Indicates if a local random seed should be used.
- local random seed: Specifies the local random seed
- show convergence plot: Indicates if a dialog with a convergence plot should be drawn.

#### ExampleProcess