Create and train a classification solution
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- UpdatedJan 30, 2025
- 6 minutes to read
- Yokohama
- AI Experiences
Specify the records used to train a classification solution, what fields trigger a prediction, and how often you want to retrain your solution.
Before you begin
- Create a custom stopwords list if needed.
- Role required: admin or ml_admin
About this task
A predictive model is only as good as the data that you use to train it. To select appropriate records for training, examine the table's database dictionary as well as the current quality of the record values that you want to use.
For information on using encrypted training data, see Data Encryption in Predictive Intelligence.
For information about the minimum and maximum number of records you can use for training, see Predictive Intelligence properties.
You must create a separate solution definition for each predictive model you want to support. The following procedure explains how to create a new classification solution, but you can also copy an existing solution definition and its configuration into a new record by selecting Copy Solution Definition from the context menu. Edit the field values on the new record as needed.
From the Yokohama release, you can also create a Workflow Classification solution using a script if you want to include an analysis of the key features influencing the model's predictions. For more information see Model Explainability.
Procedure
What to do next
In the Class Confidence section of the Solution Statistics tab in your solution, review the trained solution precision and coverage statistics.
In the Test Solutions tab in your solution, you can test the prediction output by entering values from the input fields, such as the Short Description.