Amazon Comprehend · Schema

EntityRecognizerEvaluationMetrics

Detailed information about the accuracy of an entity recognizer.

Machine LearningNatural Language ProcessingNLPText Analysis

Properties

Name Type Description
Precision object
Recall object
F1Score object
View JSON Schema on GitHub

JSON Schema

openapi.yml-entity-recognizer-evaluation-metrics-schema.json Raw ↑
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://raw.githubusercontent.com/api-evangelist/amazon-comprehend/refs/heads/main/json-schema/openapi.yml-entity-recognizer-evaluation-metrics-schema.json",
  "title": "EntityRecognizerEvaluationMetrics",
  "description": "Detailed information about the accuracy of an entity recognizer. ",
  "type": "object",
  "properties": {
    "Precision": {
      "allOf": [
        {
          "$ref": "#/components/schemas/Double"
        },
        {
          "description": "A measure of the usefulness of the recognizer results in the test data. High precision means that the recognizer returned substantially more relevant results than irrelevant ones. "
        }
      ]
    },
    "Recall": {
      "allOf": [
        {
          "$ref": "#/components/schemas/Double"
        },
        {
          "description": "A measure of how complete the recognizer results are for the test data. High recall means that the recognizer returned most of the relevant results."
        }
      ]
    },
    "F1Score": {
      "allOf": [
        {
          "$ref": "#/components/schemas/Double"
        },
        {
          "description": "A measure of how accurate the recognizer results are for the test data. It is derived from the <code>Precision</code> and <code>Recall</code> values. The <code>F1Score</code> is the harmonic average of the two scores. For plain text entity recognizer models, the range is 0 to 100, where 100 is the best score. For PDF/Word entity recognizer models, the range is 0 to 1, where 1 is the best score. "
        }
      ]
    }
  }
}

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