Model Training
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Model Training

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Article summary

Model training is the process of training the algorithm with the available historical actuals data to generate AI-driven statistical ranges for signals. You can select the required Scenario, Dimension, Month, and Signals Range from the respective fields. It is an integral step after enabling the Predict Signals functionality and selecting the Pre-computation Scenarios.

  • Planful recommends that there are at least 48 months of historical actuals data. However, the algorithm requires a minimum of 36 months of historical actuals to generate proper data-driven signals. Also, signal detection will be more effective with a greater number of historical actuals periods.

  • Once you select Start Model Training, you do not have to explicitly click Run Pre-computation on Selected Scenarios, as this process will automatically be executed as part of Model Training for the selected Scenario.

  • When you make changes to the budget/forecast data for which you had earlier run the model training, you just have to run the pre-computation and not the model training process.

  • As and when new actuals are captured by the system for the ongoing financial year, you must initiate the Model Training process to calculate signals based on the latest data. However, Planful recommends initiating the model training once every 3 to 6 months.

  • You will receive an email notification once the Model training process is completed. You will see a message on the application screen once you refresh the application post the Model training.

Note:
If there are no changes to historical actuals data and you want to update only the list of Pre-computed scenarios, you can click Run Pre-computation on Selected Scenarios. You need not run the Model Training process as long as the actuals data is not modified.



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