Execute ML Model
Description
The Execute ML Model activity allows you to apply a trained machine learning model (previously created and stored) on the selected dataset. The model can perform predictions, classifications, or other ML-based tasks depending on its type and training.
Use this activity to:
- Run a trained model on live or batch data
- Generate predictions or decisions based on model logic
- Integrate ML results into workflow pipelines for automation or analysis
Use Case:
In a loan approval pipeline, this activity can run a model trained on customer financial data to predict creditworthiness. In a retail scenario, it may classify customer feedback as positive/negative or detect fraud patterns.
Input
Not Applicable
Output
| Type | Description |
|---|---|
| Data | Model output, such as predictions or classifications |
Configuration Fields
| Field Name | Description |
|---|---|
| ML Model | Select a trained machine learning model from the ML model registry. |
| Model to use | Optional alias or reference name for the model being executed. |
Sample Input
Not applicable — input is pulled from the specified data source.
Sample Configuration
| Field | Value |
|---|---|
| ML Model | Loan_Default_Predictor_V3 |
| Model to use | LoanModel |
Sample Output
| CustomerId | CreditScore | Predicted_Default |
|---|---|---|
| 123 | 750 | No |
| 124 | 520 | Yes |
| 125 | 690 | No |