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api-reference/server-api-reference/MLSolutionAPI.md

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— title: MLSolution - Global description: The MLSolution API provides methods for handling Predictive Intelligence predictions and retrieving solution objects for all capabilities: similarity, classification, and clustering).Gets the prediction result for a classification solution and applies it to the input GlideRecord if the confidence value is higher than the threshold.Gets the capability information of a trained solution.Gets assignments for a clustering solution.Gets the cluster information for a clustering solution.Gets information for a specified clustering solution.Gets the version of the active solution.Determines if a solution is active.Gets the prediction results from the prediction server given a GlideRecord or an array of key-value pairs. locale: en-US canonical_url: www.servicenow.com/docs/r/australia/api-reference/server-api-reference/MLSolutionAPI.html release: australia product: Server API Reference classification: server-api-reference topic_type: concept last_updated: “2026-03-12” reading_time_minutes: 6

breadcrumb: [Server API reference, API reference, API implementation and reference]

MLSolution- Global

The MLSolution API provides methods for handling Predictive Intelligence predictions and retrieving solution objects for all capabilities: similarity, classification, and clustering).

This API provides methods commonly used among all solution capabilities and methods unique to classification and clustering solutions.

  • Common methods used for all solution objects:

    • getCapability()

    • getVersion()

    • isActive()

    • predict()

  • Methods only used for classification and regression solutions:

    • applyPrediction()

  • Methods only used for clustering solutions:

    • getClusterAssignments()

    • getClusterForRecord()

    • getClusterInfo()

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

The methods in this object are instantiated using MLSolutionFactory.

Parent Topic:Server API reference

Related topics

MLSolutionUtil

REST API: Get predictions for multiple solutions

MLSolution - applyPrediction(GlideRecord now_GR)

Gets the prediction result for a classification solution and applies it to the input GlideRecord if the confidence value is higher than the threshold.

Name Type Description now_GR GlideRecord GlideRecord object containing values on which to run a prediction and apply the results.

<table id=“table_iqw_pbm_yfb” class=“returns”><thead><tr><th>

Type

</th><th>

Description

</th></tr></thead><tbody><tr><td>

Boolean

</td><td>

Flag that indicates whether the prediction was applied:

  • true: Prediction applied

  • false: Prediction rejected

</td></tr></tbody> </table>“‘ var mlSolution = sn_ml.MLSolutionFactory.getSolution(“ml_incident_categorization”);

var inputGR = new GlideRecord(“incident”); inputGR.get(“0ef47232db801300864adfea5e961912”);

mlSolution.applyPrediction(inputGR);

## MLSolution - getCapability\(\)

Gets the capability information of a trained solution.

|Name|Type|Description|
|----|----|-----------|
|None| | |

<table id="table_fm3_pfx_ggb" class="returns"><thead><tr><th>

Type

</th><th>

Description

</th></tr></thead><tbody><tr><td>

String

</td><td>

Type of trained solution.Possible values:

-   Similarity
-   Classification
-   Clustering

</td></tr></tbody>
</table>

var mlSolution = sn_ml.MLSolutionFactory.getSolution(“ml_x_global_clustering”);

// configure optional parameters var options = {}; options.group_by = ‘network’; options.cluster_id = 1; options.top_n_per_cluster = 3;

if (mlSolution.getCapability() == ‘clustering’) { var results = mlSolution.getClusterAssignments(options); // pretty print JSON results gs.print(JSON.stringify(JSON.parse(results), null, 2)); }

## MLSolution - getClusterAssignments\(Object options\)

Gets assignments for a clustering solution.

<table id="table_t1q_hxt_rhb" class="parameters"><thead><tr><th>

Name

</th><th>

Type

</th><th>

Description

</th></tr></thead><tbody><tr><td>

options

</td><td>

Object

</td><td>

Optional. Values to use to narrow down the returned results by group and level within a clustering solution. Default: Return cluster memberships for all clusters.

</td></tr><tr><td>

options.group\_by

</td><td>

String

</td><td>

Optional. Identifies the segmentation field for which to retrieve cluster memberships, for example, assignment\_group.This field provides the same grouping as options provided in the **Use Group By** check box in the **Clustering Definition** form. The information provided varies based on the table selected in the **Table** field. For more information, see [Create and train a clustering solution](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/intelligent-experiences/create-clustering-solution.md).

</td></tr><tr><td>

options.cluster\_id

</td><td>

String

</td><td>

Optional. Cluster ID of a trained solution in the Cluster Summary \[ml\_cluster\_summary\] table.

</td></tr><tr><td>

options.top\_n\_per\_cluster

</td><td>

Number

</td><td>

Number of top results to receive for each cluster.

</td></tr></tbody>
</table><table id="table_u1q_hxt_rhb" class="returns"><thead><tr><th>

Type

</th><th>

Description

</th></tr></thead><tbody><tr><td>

Object

</td><td>

JSON array containing cluster information in increasing order by cluster\_id:-   cluster\_id: String. Unique cluster number within a solution of clusters.
-   rec\_display\_id: String. Record type and number.
-   rec\_sys\_id: String. Record sys\_id.
-   group\_by: If grouped, name of the segmentation field associated with this cluster.

</td></tr></tbody>
</table>

var mlSolution = sn_ml.MLSolutionFactory.getSolution(“ml_x_global_clustering”);

// configure optional parameters var options = {}; options.group_by = ‘network’; options.cluster_id = ‘1’; // returns top 3 results per cluster options.top_n_per_cluster = 3;

var results = mlSolution.getClusterAssignments(options);

Output:

[{“cluster_id”:“1”,“rec_display_id”:“Incident: INC0014483”,“rec_sys_id”:“04e33e7adb401300864adfea5e961900”,“group_by”:“network”}, {“cluster_id”:“1”,“rec_display_id”:“Incident: INC0011133”,“rec_sys_id”:“5bd23af2db401300864adfea5e96194d”,“group_by”:“network”}]

## MLSolution - getClusterForRecord\(GlideRecord now\_GR\)

Gets the cluster information for a clustering solution.

|Name|Type|Description|
|----|----|-----------|
|now\_GR|GlideRecord|Name of the input GlideRecord.|

|Type|Description|
|----|-----------|
|String|The cluster\_id from the Cluster Summary \[ml\_cluster\_summary\] table if the record belongs to a cluster. Empty string returns if the record does not belong to a cluster.|

var mlSolution = sn_ml.MLSolutionFactory.getSolution(“solution_name”); var now_GR = new GlideRecord(‘incident’); if (mlSolution.getCapability() == ‘clustering’) { var clusterId = mlSolution.getClusterForRecord(now_GR); }

## MLSolution - getClusterInfo\(Object options\)

Gets information for a specified clustering solution.

<table id="table_ak2_xcn_rhb" class="parameters"><thead><tr><th>

Name

</th><th>

Type

</th><th>

Description

</th></tr></thead><tbody><tr><td>

options

</td><td>

Object

</td><td>

Optional. Narrows down the returned results by group and level within a clustering solution. Default: Return cluster memberships for all clusters.

</td></tr><tr><td>

options.group\_by

</td><td>

String

</td><td>

Optional. Identifies the segmentation field for which to retrieve cluster memberships, for example, assignment\_group.This field provides the same grouping as options provided in the **Use Group By** check box in the **Clustering Definition** form. The information provided varies based on the table selected in the **Table** field. For more information, see [Create and train a clustering solution](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/intelligent-experiences/create-clustering-solution.md).

</td></tr><tr><td>

options.cluster\_id

</td><td>

String

</td><td>

Optional. Cluster ID of a trained solution in the Cluster Summary \[ml\_cluster\_summary\] table.

</td></tr></tbody>
</table><table id="table_bk2_xcn_rhb" class="returns"><thead><tr><th>

Type

</th><th>

Description

</th></tr></thead><tbody><tr><td>

Object

</td><td>

JSON array containing cluster information in increasing order by cluster\_id:-   cluster\_id: String. Unique cluster number within a solution of clusters.
-   cluster\_quality: String. Number from 0 to 100. Higher numbers indicate higher cluster density.
-   cluster\_size: String. Number of records in a cluster.
-   group\_by: If grouped, name of the segmentation field associated with this cluster.
-   cluster\_concept: String. Set of words that describe the cluster in descending order of frequency.

</td></tr></tbody>
</table>

var mlSolution = sn_ml.MLSolutionFactory.getSolution(“ml_x_global_clustering”);

// configure optional parameters var options = {}; options.group_by = ‘network’; options.cluster_id = 1;

var results = mlSolution.getClusterInfo(options);

Output:

[ {“cluster_id”:“1”,“cluster_quality”:“56.6”,“cluster_size”:“46”,“group_by”:“SLA”,“cluster_concept”:“issue occur capacity …”}, {“cluster_id”:“2”,“cluster_quality”:“55.47”,“cluster_size”:“75”,“group_by”:“SLA”,“cluster_concept”:“clone instance request …”}, … ]

## MLSolution - getVersion\(\)

Gets the version of the active solution.

|Name|Type|Description|
|----|----|-----------|
|None| | |

|Type|Description|
|----|-----------|
|String|Version of the active solution.|

var mlSolution = sn_ml.MLSolutionFactory.getSolution(“solution_name”);

var solutionVersion = mlSolution.getVersion();

## MLSolution - isActive\(\)

Determines if a solution is active.

|Name|Type|Description|
|----|----|-----------|
|None| | |

<table id="table_yzj_lgx_ggb" class="returns"><thead><tr><th>

Type

</th><th>

Description

</th></tr></thead><tbody><tr><td>

Boolean

</td><td>

Flag that indicates whether the solution is active.-   true: Solution active
-   false: Solution inactive

</td></tr></tbody>
</table>

var mlSolution = sn_ml.MLSolutionFactory.getSolution(“solution_name”);

var isActive = mlSolution.isActive();

## MLSolution - predict\(Object input, Object options\)

Gets the prediction results from the prediction server given a GlideRecord or an array of key-value pairs.

You can use this method to call prediction with multiple input records because GlideRecord is an iterator.

<table id="table_vv5_yfx_ggb" class="parameters"><thead><tr><th>

Name

</th><th>

Type

</th><th>

Description

</th></tr></thead><tbody><tr><td>

input

</td><td>

Object

</td><td>

[GlideRecord](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/api-reference/server-api-reference/c_GlideRecordAPI.md) or array of JSON objects containing field names and values as key-value pairs.

</td></tr><tr><td>

options

</td><td>

Object

</td><td>

Optional. JSON key-value pair with the following properties:-   top\_n: Number. If provided, returns the top results, up to the specified number of predictions.
-   apply\_threshold: Boolean. Checks the threshold value for the solution and applies it to the result set. The threshold value is solution threshold for similarity or class-level threshold for classification. Default value is true.
-   custom\_results\_filter: String. Similarity solutions only. Specifies the allowed set from which results are returned using an encoded query.

</td></tr></tbody>
</table><table id="table_khq_hgx_ggb" class="returns"><thead><tr><th>

Type

</th><th>

Description

</th></tr></thead><tbody><tr><td>

Object

</td><td>

JSON object containing the prediction results sorted by sys\_id or record\_number. -   predictedValue: String. Value representing the prediction result.
-   predictedSysId: String. The sys\_id of the predicted value. Results can be from any table on which information is being predicted.
-   confidence: Number. Value of the confidence associated with the prediction. For example, 53.84.
-   threshold: Number. Value of the configured threshold associated with the prediction.

</td></tr></tbody>
</table>

var mlSolution = sn_ml.MLSolutionFactory.getSolution(“ml_incident_categorization”);

// single GlideRecord input var input = new GlideRecord(“incident”); input.get(“0ef47232db801300864adfea5e961912”);

// configure optional parameters var options = {}; options.top_n = 3; options.apply_threshold = false;

var results = mlSolution.predict(input, options); // pretty print JSON results gs.print(JSON.stringify(JSON.parse(results), null, 2));




var mlSolution = sn_ml.MLSolutionFactory.getSolution(“ml_incident_categorization”);



// multiple GlideRecord input var input = new GlideRecord(“incident”); input.addQuery(“sys_created_onONLast week@javascript:gs.beginningOfLastWeek()@javascript:gs.endOfLastWeek()”); input.query();



// configure optional parameters var options = {}; options.top_n = 3; options.apply_threshold = false;



var results = mlSolution.predict(input, options); // pretty print JSON results gs.print(JSON.stringify(JSON.parse(results), null, 2));



Output:



{ input_gr_sys_id1: [ { predictedValue : xxx, predictedSysId : xx0, confidence : xxx, threshold : xxx



            }, 
            {
                predictedValue : yyy,
                predictedSysId : xx1,
                confidence : xxx,
                threshold : xxx
            }
    ],
input_gr_sys_id2 : [
            {
                predictedValue : xxx,
                predictedSysId : xx0,
                confidence : xxx,
                threshold : xxx

            }, 
        ...
    ]



}






var mlSolution = sn_ml.MLSolutionFactory.getSolution(“ml_incident_categorization”);



// key-value pairs input var input = [{“short_description”:“my email is not working”}, {short_description:“need help with password”}];



// configure optional parameters var options = {}; options.top_n = 3; options.apply_threshold = false;



var results = mlSolution.predict(input, options); // pretty print JSON results gs.print(JSON.stringify(JSON.parse(results), null, 2));



“‘



    
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