Finding data outliers

With Encord Active, you can quickly find data and label outliers for pre-defined metrics, custom metrics, and label classes. Encord Active finds outliers using precomputed Interquartile ranges.

Data outliers

1. Find outliers

Navigate to the Data Quality > Summary tab. Here, the Quality 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 tags 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.

Label outliers

Steps

1. Find outliers

Navigate to the Label Quality > Summary tab. Here each Quality Metric will be presented as an expandable panes.

You can click on a metric to get a deeper insight into moderate outliers and severe outliers. Severe outliers are presented first in the pane.

2. Tag outliers

Next, you can use the slider to navigate your data from most severe outlier to least severe.

When you have identified outliers of interest use the tags or bulk tagging feature to select 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.

Within the Actions tab, click Filter data frame on and select tags. Next, choose the tags you would like to export, relabel, augment, review, or delete from your dataset.