Create and train a solution definition Specify the records used to train a predictive model, what fields trigger a prediction, and how often to retrain a solution. Before you beginRole required: admin or ml_admin. About this task A predictive model is only as good as the data you use to train it. To select appropriate training records, you should be familiar with the table database dictionary as well as the current quality of the record values to be used. You must create a separate solution definition for each predictive model you want to support. Procedure Navigate to Agent Intelligence > Solution Definitions. The system displays the current list of solution definitions. Click New. The system displays a blank solution definition form. Enter these field values. Field Description Solution template Select a template to fill in the form with preset values. For example, the Incident Assignment Template selects the Incident table and creates a filter that selects resolved or closed incidents within the last 12 months.Note: This field cannot have a value of None. By default, Agent Intelligence offers these solution templates. Assignment Template Category Template Incident Assignment Template Incident Category Template Incident Priority Template Priority Template Table Select the table containing the target records to be predicted. Domain On instances where domain separation is active, select the domain whose target records you want to predict. Create a separate solution definition record for each domain whose field values you want to predict. Label Enter a name for the solution record. Name The system generates the value of this read-only field based on the Label. Active Select whether the system uses the solution definition record to train solutions. You can only train active solution definition records. Filter Select the conditions you want to apply to the training records. In order to train a solution, the filter must return at least one record. If your filter returns no records, update it until it returns records for training. The system provides a default filter when you select a Solution Template. A solution is only as good as the data you use to train it. In general, a good filter has these characteristics. The training records are inactive and have task states that represent completing work within your standard process such as resolved or closed. The training records only contain correct values for the target field. Filter out records with unreliable target field values. The training records contain multiple examples of each target field value you want the solution to predict. The training records include common variations of the input fields. For example, the Incident Category Template creates a filter with these conditions. [Created][on][Last 12 months] AND [Active][is][false] AND [State][is one of][Resolved | Closed] Input fields Select the input fields you want the solution to use to generate a prediction. The system provides default input fields when you select a Solution Template. In general, good input fields have these characteristics. The fields are available to users when creating records. Configure the form to display all input fields. The field data type is string. The more information a field provides, the more often a solution can make a prediction, and the more often predictions are accurate. The field has a default value. The field should not have a blank value. For example, all default solution definitions use the Short description field as the input field. Output field Select the field whose value you want the predictive model to set. The system provides a default output field when you select a Solution Template. In general, a good output field has these characteristics. The field is a choice field or a string field with a finite set of possible values. The field has some casual connection to the input fields. For example, the Incident Category Template selects the Category field. Training frequency Select how often the system regenerates the solution based on records matching the Filter. Options include: Run Once Every 30 days Every 60 days Every 90 days Every 120 days Every 180 days By default, the system runs training once. This allows you to review and update the solution definition as needed until it provides acceptable coverage and precision values. Click the appropriate button for the solution definition. OptionDescription Activate & Train Activate and train a default solution definition. Submit & Train Create a new solution definition record and train it. The system displays the Training Activation confirmation window. Click OK to confirm. The system schedules the solution for training with the nearest training service. When training is complete, the system uploads the solution as an Attachment record. What to do nextReview the trained solution precision and coverage statistics.