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Definition

The quasi-constant features test allows you to specify if a certain feature is expected to be near-constant (low variance) or not.

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Taxonomy

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

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Why it matters

  • Quasi-constant features have very low variance and tend to not be as useful for models.
  • If a feature shouldn’t be quasi-constant but is, you might want to re-normalize it.

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Test configuration examples

If you are writing a tests.json, here are a few valid configurations for the character length test: 
[
  {
    "name": "Feature 'Year' is not quasi-constant",
    "description": "Asserts that the feature 'Year' does not have a very low variance",
    "type": "integrity",
    "subtype": "quasiConstantFeature",
    "thresholds": [
      {
        "insightName": "featureProfile",
        "insightParameters": [
            {"name": "name", "value": "Year"} // Selects feature `Year`
        ],
        "measurement": "isQuasiConstant",
        "operator": "is",
        "value": False
      }
    ],
    "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
  }
]
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