Skip to main content

Documentation Index

Fetch the complete documentation index at: https://openlayer.com/docs/llms.txt

Use this file to discover all available pages before exploring further.

​
Definition

The empty feature count test allows you to set a threshold on the number of features that have only null (missing) values.

​
Taxonomy

  • Task types: Tabular classification, tabular regression.
  • Availability: and .

​
Why it matters

  • Empty features contain no information and can indicate that there is a problem with the data collection/ingestion process.

​
Test configuration examples

If you are writing a tests.json, here are a few valid configurations for the character length test: 
[
  {
    "name": "No empty features",
    "description": "Asserts that there are no empty features",
    "type": "integrity",
    "subtype": "emptyFeatureCount",
    "thresholds": [
      {
        "insightName": "emptyFeatures",
        "insightParameters": null,
        "measurement": "emptyFeatureCount",
        "operator": "is",
        "value": 0
      }
    ],
    "subpopulationFilters": null,
    "mode": "development",
    "usesValidationDataset": true, // Apply test to the validation set
    "usesTrainingDataset": false,
    "usesMlModel": false,
    "syncId": "b4dee7dc-4f15-48ca-a282-63e2c04e0689" // Some unique id
  }
]