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AI & Machine Learning · Foundational

Label

The known target value attached to a training example that a supervised model learns to predict.

Definition

Labels, also called targets or ground truth, are the answers in supervised learning. They may be class names for classification or numbers for regression. Label quality directly limits model quality, so labeling processes often use multiple annotators and consensus.

Example

The fraud/not-fraud column in a transactions dataset.

Exam tip

Noisy or inconsistent labels cap achievable accuracy no matter how good the algorithm is.

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