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Model overview

The models overview gives an overview of all your models in production in one place together with their main metrics:
Every model in the models overview consists of 5 components:
  1. 1.
    Model name To get a more in-depth analysis of the model, click on this name. This name can be changed in the model settings.
  2. 2.
    Main performance metrics These are a summary of the most critical metrics. It shows the name of metric and the realized and estimated values.
  3. 3.
    Summary performance metrics These summarises the performance status of the model on the realized and estimated metrics. If available, when hovering you can see more information about other metrics.
  4. 4.
    Summary of data drift results These summarises the status of results from concept shift, covariate shift and data quality. When hovering and clicking you can see more information these results.
  5. 5.
    Monitoring Status This indicates whether or not the last run of NannyML was successful, i.e., whether the latest run was executed. These are the possible states:
    • Successful: when the most recent run didn't have any errors.
    • Error: when the most recent run did have errors.
    • Empty: when the model was newly created and there are no results yet.
    • Skipped run: when no new data was added the run was skipped. The results would still be the same: Alerts/No Alerts/Empty.
    What an 'error' means:
    • There was an exception when running NannyML calculators.
    • Something else went wrong that prevented us from running NannyML, e.g., a timeout when starting a new job to run.