​
Definition

The PPS is a metric that measures the predictive power of a feature with respect to the label/target. It has similarities with the Pearson correlation coefficient, but can also capture non-linear relationships. The PPS tests allows you to set a threshold on the PPS for a specific feature.

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Taxonomy

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

​
Why it matters

  • Features with a low PPS score are likely to be redundant and can be removed from the dataset.

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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": "PPS for feature 'Age' greater than 0.7",
    "description": "Asserts that the predictive power score of feature 'Age' is greater than 0.7",
    "type": "integrity",
    "subtype": "ppScoreValueValidation",
    "thresholds": [
      {
        "insightName": "ppScore",
        "insightParameters": [{ "name": "name", "value": "Age" }], // Selects feature `Age`
        "measurement": "ppScoreValue",
        "operator": ">",
        "value": 0.7
      }
    ],
    "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
  }
]

​
Definition

The PPS is a metric that measures the predictive power of a feature with respect to the label/target. It has similarities with the Pearson correlation coefficient, but can also capture non-linear relationships. The PPS tests allows you to set a threshold on the PPS for a specific feature.

​
Taxonomy

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

​
Why it matters

  • Features with a low PPS score are likely to be redundant and can be removed from the dataset.

​
Test configuration examples

If you are writing a tests.json, here are a few valid configurations for the character length test:

[
  {
    "name": "PPS for feature 'Age' greater than 0.7",
    "description": "Asserts that the predictive power score of feature 'Age' is greater than 0.7",
    "type": "integrity",
    "subtype": "ppScoreValueValidation",
    "thresholds": [
      {
        "insightName": "ppScore",
        "insightParameters": [{ "name": "name", "value": "Age" }], // Selects feature `Age`
        "measurement": "ppScoreValue",
        "operator": ">",
        "value": 0.7
      }
    ],
    "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
  }
]