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Creating a genetic algorithm model

Updated on July 5, 2022

Create a genetic algorithm model while you are building predictive models to generate highly predictive, non-linear models. A genetic algorithm solves optimization problems by creating a generation of possible solutions to the problem.

Run the model for multiple generations and save the best model. For example, you can use the genetic algorithm model in trading scenarios to project possible series of buy and sell actions.
  1. In the Model creation step, from the Create model drop-down list, click Genetic algorithm.
  2. In the Create Genetic Algorithm model workspace, enter a Name and a Description. Click Create model.
  3. In the Run settings section, specify how many generations of models you want to run:
    • , .
    If you want to stop after a specified number of generations, select Number of generations and enter the number of generations. Click Run.
    Note: Consecutive runs always continue to improve the result of the previous run. To try to achieve a higher performance, run the algorithm for an additional number of generations.
    If you want to stop generating models when the performance increase on the validation set for a specified number of generations is below the specified value, perform the following actions:
    1. Select the Early stopping option.
    2. Enter a value for the minimum performance increase.

      The default value is 0.01.

    3. Enter the number of generations for which there is no minimum performance increase on the validation set. Click Run.
  4. When you get a model with the expected performance, click Submit.
Result: The best performing model from the last generation is saved and added to the list in the Model creation step.

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