PredictabilityEstimateStore - Global

Enables storing and retrieving predictability estimates.

The PredictabilityEstimateStore API requires the Predictive Intelligence plugin (com.glide.platform_ml) and is provided within the sn_ml namespace.

PredictabilityEstimateStore - add(Object mlEstimate)

Adds a new predictability estimate object to the store and returns a unique name.

Note:

Label values do not need to be unique. For example, if you run this method with the same label 10 times, this method adds 10 different uniquely-named objects to the store.

Table 1. Parameters

Name	Type	Description
mlEstimate	PredictabilityEstimate	PredictabilityEstimate() object to add to the store.

Table 2. Returns

Type	Description
String	System-generated predictability estimate name.

The following example shows how to add a predictability estimate to the store. Use PredictabilityEstimate - submitTrainingJob() to run the training job after adding it to the store.

// Create a dataset 
var myData = new sn_ml.DatasetDefinition({

  'tableName' : 'incident',
  'fieldNames' : ['assignment_group', 'short_description', 'description'],
  'encodedQuery' : 'activeANYTHING'

});

// Create an estimate 
var myEstimate = new sn_ml.PredictabilityEstimate({

  'label': "my estimate definition",
  'dataset' : myData,
  'predictedFieldName' : 'assignment_group',
  'inputFieldNames':['short_description']

});

// Add the estimate to the store to later be able to retrieve it.
var my_unique_name = sn_ml.PredictabilityEstimateStore.add(myEstimate);

PredictabilityEstimateStore - deleteObject(String name)

Removes a specified predictability estimate object from the store.

Table 3. Parameters

Name	Type	Description
name	String	Name of the PredictabilityEstimate() object to be deleted.

Table 4. Returns

Type	Description
None

The following example shows how to delete a predictability estimate from the store.

sn_ml.PredictabilityEstimateStore.deleteObject("ml_sn_global_global_estimate");

PredictabilityEstimateStore - get(String name)

Gets a predictability estimate object from a store.

Table 5. Parameters

Name	Type	Description
name	String	Name of a predictability estimate in a store.

Table 6. Returns

Type	Description
Object	PredictabilityEstimate object. Returns an error if the object does not exist.

The following example shows how to get a predictability estimate object from the store using the get() method and view its training status using the PredictabilityEstimate - getActiveVersion() and PredictabilityEstimateVersion - getStatus() methods.

// Get status
var mlEstimate = sn_ml.PredictabilityEstimateStore.get('ml_incident_categorization');

gs.print(JSON.stringify(JSON.parse(mlEstimate.getActiveVersion().getStatus(), null, 2)));

Output:

{
 "state":"solution_complete",
 "percentComplete":"100",
 "hasJobEnded":"true"
}

PredictabilityEstimateStore - getAllNames(Object options)

Gets the names of all predictability estimate definition records in the store.

Table 7. Parameters

Name	Type	Description
options	Object	Options for restricting results within the specified properties. { "label": "String", "domainName": "String", "scope": "String" };
options.label	String	Optional. Label of your solution object.
options.domainName	String	Optional. Name of the domain for your solution object. Refer to Domain separation and Predictive Intelligence.
options.scope	String	Optional. Name of an application scope for your solution object.

Table 8. Returns

Type	Description
Array	List of strings representing predictability estimate object names in the store.

In the following example, the getAllNames() method returns a list of all names in the store.

gs.print(JSON.stringify(JSON.parse(sn_ml.PredictabilityEstimateStore.getAllNames()), null, 2));

Output:

[
  "ml_x_snc_global_global_predictability_estimate_1",
  "ml_x_snc_global_global_predictability_estimate",
  "ml_x_snc_global_global_predictability_estimate_2",
  "ml_x_snc_global_global_my_estimate_definition"
]

In the following example, the getAllNames() method returns only names associated with values set in the options parameter.

var options = {
  'label' : 'my estimate definition',
  'domainName' : 'global',
  'scope' : 'global'
};
var solNames = sn_ml.PredictabilityEstimateStore.getAllNames(options);
gs.print(JSON.stringify(JSON.parse(solNames), null, 2));

Output:

[
  "ml_x_snc_global_global_my_estimate_definition"
]

PredictabilityEstimateStore - update(String name, Object mlEstimate)

Updates a predictability estimate object in a store.

Table 9. Parameters

Name	Type	Description
name	String	Name of the predictability estimate to update.
mlEstimate	PredictabilityEstimate	PredictabilityEstimate() object properties to update.

Table 10. Returns

Type	Description
None

The following example shows how to update a predictability estimate object in the store.

var estimateUpdate = new sn_ml.PredictabilityEstimate({
  'label': 'my estimate definition',
  'dataset' : myData,
  'predictedFieldName' : 'assignment_group',
  'inputFieldNames': ['short_description']
});

sn_ml.PredictabilityEstimateStore.update('ml_sn_global_global_incident_service', estimateUpdate);