Finding Data Outliers
Find outliers in your dataset using Encord Active's Data Quality tab
With Encord Active, you can quickly find image outliers for pre-defined metrics, custom metrics, and label classes. Encord Active finds outliers using precomputed Interquartile ranges.
If you haven't installed Encord Active, visit installation. In this workflow we will be using the BDD validation dataset.
1. Find outliers
Navigate to the Data Quality > Summary tab. Here, the metrics will be presented as expandable panes.
Click on a metric to get deeper insight into moderate outliers and severe outliers. The most severe outliers are presented first in the pane.
Use the slider to navigate your data from most severe outlier to least severe.
2. Tag outliers
When you have identified outliers of interest, use the tagging or bulk tagging feature to save a group of images.
After creating a tagged image group, you can access it at the bottom of the left sidebar in the Actions tab.
3. Act on outliers
Within the Actions tab, click Filter dataframe on and select tags. Next, choose the tags you would like to export, relabel, augment, review, or delete from your dataset.