Get Predictions in REST APIs

POST /services/data/v63.0/ssot/machine-learning/predict

GET /services/data/v61.0/ssot/machine-learning/configured-models/{ModelIdOrName}

Note You can use the predictive model name (this example) or model id (API Name). Some APIs also require the model API name “{ModelIdOrName}”. You can find a model's API name in Model Builder, on the model details page.

Let's look at the REST request using the Predicted Purchased model.

{
    "model": 
    {
        "name": "Predicted_Purchased_CM_12l_YSs01128465"
    },
    "type": "RawData",
    "fieldNames": ["Industry_c__c", "Response_Time_From_Assignment_c__c" , "Company_c__c", "Title_c__c"],
    "rows": 
    [
        ["High Tech", 56, "Condax","Student"],
        ["Professional Services",70,"Rantouch","Developer"]
    ],
    "settings" : {
        "maxPrescriptions" : 3,
        "maxTopFactors" : 2,
        "prescriptionImpactPercentage" : 50
    }
    
 }

• maxPrescriptions specifies the maximum number of improvements (1-3) to return in the response
• maxTopFactors specifies the number of top predictors (1-3) to return in the response
• prescriptionImpactPercentage specifies the threshold filter (minimum % improvement for the outcome, which in this example is 50%) needed for the improvement to be returned in the response

{
  "aggregatePredictions": [],
  "model": {
    "id": "12l1Q000000blV0QAI"//Id
  },
  "predictionType": "BinaryClassification",
  "predictions": [
    {
      "factors": [
        {
          "fields": [
            {
              "customText": null,
              "inputValue": "Student",
              "label": null,
              "name": "Title_c__c",
              "prescribedValue": "Title"
            }
          ],
          "value": -40.58208510642879
        },
        {
          "fields": [
            {
              "customText": null,
              "inputValue": "56",
              "label": null,
              "name": "Response_Time_From_Assignment_c__c",
              "prescribedValue": "Response Time From Assignment"
            }
          ],
          "value": 10.187649697792125
        }
      ],
      "partition": {
        "id": "12l1Q000000blV0QAI" //Id"
      },
      "predictedValue": 0.5997765233332488,
      "prescriptions": [],
      "status": "Success",
      "type": "BinaryClassification",
      "warnings": {
        "missingFieldNames": [],
        "outOfBoundsFields": []
      }
    },
    {
      "factors": [
        {
          "fields": [
            {
              "customText": null,
              "inputValue": "Developer",
              "label": null,
              "name": "Title_c__c",
              "prescribedValue": "Title"
            }
          ],
          "value": -28.000138322513255
        },
        {
          "fields": [
            {
              "customText": null,
              "inputValue": "70",
              "label": null,
              "name": "Response_Time_From_Assignment_c__c",
              "prescribedValue": "Response Time From Assignment"
            }
          ],
          "value": 6.156639498073147
        }
      ],
      "partition": {
        "id": "12l1Q000000blV0QAI" //Id"
      },
      "predictedValue": 5.278021902657085,
      "prescriptions": [],
      "status": "Success",
      "type": "BinaryClassification",
      "warnings": {
        "missingFieldNames": [],
        "outOfBoundsFields": []
      }
    }
  ],
  "settings": {
    "aggregateFunctions": [],
    "maxPrescriptions": 3,
    "maxTopFactors": 2,
    "prescriptionImpactPercentage": 50
  }
}