Get Predictions in Apex

You can programmatically run predictions in Apex using the ConnectApi.SmartDataDiscovery.predict method. There are two types of input:

• record IDs
• record IDs plus calculated fields that are not stored in the record

This function accepts an input of up to 200 record IDs or raw data rows, along with a prediction definition ID. It returns up to 200 predictions of type ConnectApi.SmartDataDiscoveryPrediction.

Note Before you use the Apex Predict API, deploy the model you want to use for predictions. For instructions, see Deploy Models.

For more information about Apex code, see the Apex Developer Guide.

Permissions Required to View Predictions and Improvements

To view predictions, improvements, and related details, users must have the View Einstein Discovery Recommendations permission assigned to their Salesforce account. To learn more, see Assign Einstein Discovery Permission Sets to Users.

API Usage Limits

• ConnectApi.SmartDataDiscovery.predict can be called up to 2,000 times per user per hour.
• Each ConnectApi.SmartDataDiscovery.predict can handle up to 200 records in a single call.
• ConnectApi.SmartDataDiscovery.predict can be called no more 50,000 times per day (24 hours) per org.

Batch Apex and Callouts for Models Using Supplemental Datasets

For batch Apex, if you are using a model associated with a supplemental dataset (see Map Model Variables), be sure to follow the requirements for callouts described in Callout Limits and Limitations in the Apex documentation.

Get Predictions Using the Record ID as Input

Syntax

public ConnectApi.SmartDataDiscoveryPrediction ConnectApi.SmartDataDiscovery.predict(ConnectApi.SmartDataDiscoveryPredictInputRecords input)

SmartDataDiscoveryPredictInputRecords class

Get Predictions Using the Record ID and Calculated Fields as Input

Syntax

public ConnectApi.SmartDataDiscoveryPrediction ConnectApi.SmartDataDiscovery.predict(SmartDataDiscoveryPredictInputRecordOverrides input)

SmartDataDiscoveryPredictInputRecordOverrides class

ConnectApi.SmartDataDiscoveryPredictInputRowObject class

ConnectApi.SmartDataDiscoveryDiscoveryPredictSettings class

Output Classes

ConnectApi.SmartDataDiscoveryPrediction class

ConnectApi.SmartDataDiscoveryPredictObject class

ConnectApi.SmartDataDiscoveryPredict class

ConnectApi.SmartDataDiscoveryPredictCondition class

ConnectApi.SmartDataDiscoveryPredictColumn class

Connectapi.SmartDataDiscoveryPredictImportWarnings class

Connectapi.SmartDataDiscoveryPredictOutOfBoundsFields class

Exceptions

If there are rows that caused the prediction method to fail, this call returns an exception rather than a prediction.

ConnectApi.SmartDataDiscoveryPredictErrorObject class

Code Example

This code example is designed for building test cases.

// Initialize the Prediction API Input Record
ConnectApi.SmartDataDiscoveryPredictInputRecords predictInput = new ConnectApi.SmartDataDiscoveryPredictInputRecords();

// Set Prediction Definition
predictInput.predictionDefinition = '1ORB0000000TN1SOAW';

// Set Records
predictInput.records = new List<Id>{'006B0000004ApAZIA0'};

// Set Settings for Prediction
ConnectApi.SmartDataDiscoveryDiscoveryPredictSettings settings = new ConnectApi.SmartDataDiscoveryDiscoveryPredictSettings();
settings.maxMiddleValues = 3;//[0-3] limit of 3
settings.maxPrescriptions = 3;
settings.prescriptionImpactPercentage = 20;
predictInput.settings = settings;
////////////////////////////////////////////////////////////////

// Generate Predictions
ConnectApi.SmartDataDiscoveryPrediction response = ConnectApi.SmartDataDiscovery.predict(predictInput);
// Get Prediction
ConnectApi.SmartDataDiscoveryPredictObject prediction = (ConnectApi.SmartDataDiscoveryPredictObject) response.predictions[0];
// Get Prescriptions (Improvements)
List<ConnectApi.SmartDataDiscoveryPredictCondition> prescriptions = prediction.prescriptions;

// Iterate over the first prescription
ConnectApi.SmartDataDiscoveryPredictCondition first_prescription = prescriptions[0];
Double value = first_prescription.value;
List<ConnectApi.SmartDataDiscoveryPredictColumn> columns = first_prescription.columns;

// Prescriptions usually have one-column information:
ConnectApi.SmartDataDiscoveryPredictColumn column_1 = columns[0];

String columnName = column_1.columnName;
String columnValue = column_1.columnValue;
String columnInputVal = column_1.inputValue;
////////////////////////////////////////////////////////////////

// Get Top Factors (Top Predictors)
List<ConnectApi.SmartDataDiscoveryPredictCondition> topFactors = prediction.prediction.middleValues;
// Iterate over the first TopFactor
ConnectApi.SmartDataDiscoveryPredictCondition first_topFactor = topFactors[0];

Double tf_value = first_topFactor.value;
List<ConnectApi.SmartDataDiscoveryPredictColumn> tf_columns = first_topFactor.columns;
  
// Top Factors have multiple Columns, so it is recommended to iterate over the list
ConnectApi.SmartDataDiscoveryPredictColumn tf_column_1 = tf_columns[0];

String tf_columnName = tf_column_1.columnName;
String tf_columnValue = tf_column_1.columnValue;
String tf_columnInputVal = tf_column_1.inputValue;
////////////////////////////////////////////////////////////////

// Get Import Warnings
ConnectApi.SmartDataDiscoveryPredictImportWarnings importWarnings = prediction.prediction.importWarnings;

// System Debug
System.debug('Total ' + prediction.prediction.total);  
System.debug('Import Warnings ' +importWarnings);