Error classification in GraphQL

Introduction

Error classification helps us understand what kind of mistakes happen in data or models. This way, we can fix problems better and improve results.

When checking if a model predicts correctly or not

When finding out what types of mistakes a model makes

When improving a system by focusing on common errors

When reporting how well a model works in simple terms

Syntax

GraphQL

type ErrorClassification {
  truePositive: Int
  trueNegative: Int
  falsePositive: Int
  falseNegative: Int
}

This GraphQL type defines common error categories in classification tasks.

Each field holds a count of that error type.

Examples

This query asks for counts of true positives and false negatives.

GraphQL

query GetErrorCounts {
  errorClassification {
    truePositive
    falseNegative
  }
}

This variation adds common performance metrics to the error classification type.

GraphQL

type ErrorClassification {
  accuracy: Float
  precision: Float
  recall: Float
}

Sample Program

This query fetches all four main error counts from a GraphQL API that tracks classification errors.

GraphQL

query {
  errorClassification {
    truePositive
    trueNegative
    falsePositive
    falseNegative
  }
}

Important Notes

True Positive means the model correctly predicted a positive case.

False Negative means the model missed a positive case.

Counting these errors helps improve model accuracy and trust.

Summary

Error classification breaks down model mistakes into clear groups.

This helps find where the model does well or needs work.

GraphQL can be used to query these error counts easily.