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Precision

Definition

The number of true positive results divided by the number of all positive results, including those not identified correctly.

Deep Dive

Precision is a crucial evaluation metric in classification models that quantifies the accuracy of the positive predictions made by the model. It is calculated as the ratio of true positive results (correctly identified positive instances) to the total number of positive results predicted by the model (which includes both true positives and false positives). In simpler terms, precision answers the question: "Of all the instances the model predicted as positive, how many were actually positive?"

Examples & Use Cases

  • 1In a spam filter, high precision means very few legitimate emails are incorrectly marked as spam
  • 2In a fraud detection system, high precision means fewer legitimate transactions are flagged as fraudulent
  • 3In a product recommendation system, high precision means recommended products are highly relevant to the user

Related Terms

RecallF1-scoreAccuracy

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