Perform Prediction

This page is accessed via:

• Buy Shipment > Actions > Logistics Machine Learning > Perform Prediction
• Order Release > Actions > Logistics Machine Learning > Perform Prediction

Note: The actions Load Data into Analytics, and Perform Training must be completed before running this action.

Note: Only up to 15 shipments/order releases can be predicted simultaneously. This limit will be extended in a future release.

Note: Use of an external service to connect to IoT IA services has been deprecated and will be removed in a future release. IoT IA is being replaced by Embedded Learning.

The Perform Prediction action sends either sends all buy shipment information or order release information to the machine  attributes and event attributes along with the necessary scenario information to the machine learning service. For ETA Prediction based on the request, embedded learning (EML) provides the Predicted Transit Time for the selected shipment. The action populates the Predicted Arrival Time on the last Dropoff stop of the shipment. Once the prediction data is received from the machine learning service, this action populates the analytics prediction tables in Transportation Intelligence.

1. Select one or more buy shipments or order releases.
2. Select Actions > Logistics Machine Learning > Perform Prediction. The Perform Prediction action opens the Prediction Input page where the following input is required:
   1. Enter a machine learning Project ID.
   2. Select a Scenario Model Type.
      • If the machine learning project has an Objective Model Type of Planned ETA Prediction, you see a single option of Planned Model.
      • If the machine learning project has an Objective Model Type of Order Route Prediction, you see a single option of Order Route Prediction.
   3. Select a Scenario ID from the resulting list. This list is empty if the specified project ID has no scenarios for which the Perform Training action was completed.
   4. Click Perform Prediction.

When the prediction is in process, you see the Prediction Results page that may include the following information in the Prediction Status section:

• Project ID
• Scenario ID
• Status: ACCEPTED, PROCESSING, COMPLETED, or FAILED

When the prediction is complete, a Shipment Predictions section is added to the page and it contains:

• Shipment ID
• Event ID (depending on the Scenario Object Model Type selected): This is the tracking event ID.
• Accuracy: This is the accuracy of the model used in the prediction. Accuracy is displayed in decimals.
• Predictions: This column lists the predicted transit time of the shipment. Prediction interval provides a range of values that predicts the value of a new observation, based on your existing model. A 95% prediction interval of 9H 30M and 10H 30M tells you that future transit time for shipments with similar attributes will fall into that range 95% of the time. There is a 5% chance that a transit time will not fall into this interval.
• Prediction Low Value: Indicates the lower end of the prediction interval.
• Prediction High Value: Indicates the higher end of the prediction interval.

If the prediction failed, you see a Failure Reasons section with details of what went wrong.