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# Configure DBSCAN for a clustering solution

# Configure DBSCAN for a clustering solution {#ariaid-title1}

* Versão de lançamento: Australia
* 
* Atualizado 12 de mar. de 2026
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 1 min. de leitura

Consider applying the Density Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to your clustering solution. DBSCAN is available as an alternative to the default clustering algorithm, k-means.

## Antes de Iniciar

Nota:  
Configuring advanced settings on your ML solutions is optional. If you choose to configure any of these settings, make sure you're well informed regarding the technology you're enabling in the solution, and that your use case benefits from what the technology offers. For more information, see the [Dive deeper with Clustering Advanced Parameters](https://www.servicenow.com/community/intelligence-ml-articles/dive-deeper-with-clustering-advanced-parameters/ta-p/2695847) article on ServiceNow Community.  
* Create a clustering solution definition or use an existing one.
* Role required: admin or ml_admin
{#configure-dbscan-for-clustering-solution__ul_usd_cst_1kb}

## Por Que e Quando Desempenhar Esta Tarefa

Predictive Intelligence uses the k-means algorithm by default in its
clustering framework. DBSCAN is another clustering algorithm that's also used in
data mining and machine learning. Some users prefer DBSCAN as it doesn't require you
to specify the number of clusters in the data before clustering. For a summary of
the pros and cons for each algorithm, see this [conversation](https://www.researchgate.net/post/What_is_the_difference_between_K-MEAN_and_density_based_clustering_algorithm_DBSCAN) and this [article](https://medium.com/@soroushhashemifar/kmeans-vs-dbscan-d9d5f9dbee8b).

In this example scenario, you apply DBSCAN to a clustering solution.

## Procedimento

1. Navigate to AllPredictive IntelligenceClusteringSolution Definitions.
2. Open a clustering solution definition form.  
   In this example scenario, you use an Incidents clustering solution definition form.  
3. On the Advanced Solution Settings tab in the Related Links section of the form, select Solution Parameters from the picker, then click New.  
4. Create a parameter record.
   1. In the Solution Parameters field, select the search icon.
   2. In the ML Solution Parameters screen, select Use DBSCAN algo for clustering.  
   {#configure-dbscan-for-clustering-solution__substeps_ow5_5tj_zjb}
5. Select Submit.  
   The Advanced Solution Setting record appears. The field User Inputs is grayed out because it does not apply to this algorithm.  
6. Select Submit.  
   Result: DBSCAN is configured for your clustering solution. Its solution parameter appears on the Advanced Solution Settings tab of your clustering solution definition form.  
**Tarefas relacionadas**   

* [Create and train a clustering solution](https://servicenow-prod.fluidtopics.net/ecYIQ6D0OLyg_ddAGlsYCA "Group similar records into clusters so you can address them collectively or identify patterns.")