Interacting with Monte Carlo's Detectors

Monte Carlo offers three main customization tools to control, tune, and influence our automatic ML detectors

• Sensitivity Settings
• Share Feedback
• Exclusion Windows

Sensitivity Settings

Monte Carlo allows you to change the sensitivity of our models to increase or decrease the likelihood of generating an incident based on anomalous behavior. High sensitivity will generate more incidents and is best for your most important tables. Low sensitivity will generate fewer incidents and is best for less important tables or tables that have generated historical noisy incidents.

See https://docs.getmontecarlo.com/docs/sensitivity-settings for more information.

Share Feedback

Our machine learning (ML) models use your feedback to learn and improve. We are continually working to enhance these models, and customer feedback assists us in making further improvements.

See https://docs.getmontecarlo.com/docs/share-feedback for more information.

Exclusion Windows

When you have a service provider outage or an integration issue between Monte Carlo and your data sources, you might have an undesirable gap in detection that causes incorrect detection or reduces the sensitivity of Monte Carlo's anomaly detection.

While Monte Carlo's ML models know how to handle weird data patterns which can arise to some extent there is the known ML saying “garbage in, garbage out” and we are aware that sometimes issues occur, either on our side or yours.

See https://docs.getmontecarlo.com/docs/exclusion-windows and go to Settings > Filters > Exclusion Windows in the app to get started.