A genetic algorithm solves optimization problems by creating a generation of possible solutions to the problem. Create a genetic algorithm model while you are building predictive models to generate highly predictive, non-linear models. 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.
In the Model creation step, click Create model > Genetic algorithm.
In the Summary section, enter a name for the model and, optionally, a description of the model.
In the Run settings section, specify how many generations of models you want to run:
Select the Number of generations option to stop after a specified number of generations.
Enter the number of generations and click Run.
Consecutive runs always continue to improve the result of the previous run. To try to achieve a higher performance, you can run the algorithm for an additional number of generations.
Select the Early stopping option to stop generating models when the performance increase on the validation set for a specified number of generations is below the specified value.
Enter a value for the minimum performance increase. The default value is 0.01.
Enter the number of generations for which there is no minimum performance increase on the validation set and click Run.
When you get a model with the expected performance, click Submit. The best performing model from the last generation is saved and added to the list in the Model creation step.