Key questions about this property
The answers below summarize the purpose, scope, default effect, and review scenarios for this property.
| What does it do? |
It configures the sensitivity level for detecting anomalies in Discovery schedules, affecting how many anomalies are reported based on the chosen sensitivity. |
| What area does it affect? |
Discovery Admin Workspace |
| What does the default mean? |
The default value is "low", which is the baseline setting used unless it is changed. |
| When should you review it? |
Review this property when tuning anomaly detection to optimize accuracy based on operational needs. |
Out of the box property record
Raw metadata from the property record.
| Property name |
sn_disco_workspace.discovery_schedule_anomaly_ml_model_sensitivity |
| Sys ID |
e1204b0dff9c62103612ffffffffffaa |
| Type |
choice list |
| Application |
Discovery Admin Workspace |
| Default value |
low |
| Description |
Advanced setting to adjust the sensitivity for ML-based Discovery schedule anomaly detection. Please note that changing the sensitivity model can impact the accuracy of detection. Lower sensitivity will result in more anomalies reported that could result in more false positives (scans that are not anomalies may be reported as anomalies). Higher sensitivity will result in fewer anomalies being reported that could result in more false negatives (scans that are true anomalies may not be reported). The default value is low. |
| Updated |
2025-04-05 19:45:29 |
Sources
Official references and nearby text excerpts where this property appears.
Context preview
Snippet 1
... company names, product names, and logos may be trademarks of the respective companies with which they are associated. 1020 Field Description • Type: string • Default value: CIs, Cloud Resources sn_disco_workspace.discovery_schedule_anomaly_ml_model_sensitivity Discovery Admin Workspace: Adjusts the sensitivity for ML-based Discovery schedule anomaly detection. Changing the sensitivity can impact detection accuracy. Lower sensitivity results in more anomalies reported, which could increase false ...
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