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Artificial Intelligence & Machine Learning vocabulary · Evaluation and Metrics

Accuracy

Meaning in artificial intelligence & machine learning, with examples

/ˈækjərəsi/nounCore term

In artificial intelligence & machine learning, accuracy means: The share of a model's predictions that are correct, out of all its predictions. A model with 90% accuracy is right on nine of every ten examples.

In Turkish: doğruluk, doğruluk oranı

How it is used

The simplest classification metric and often the first one reported. It can mislead when classes are imbalanced: if 99% of emails are not spam, a model that never says 'spam' still reaches 99% accuracy.

Example sentences

  1. Accuracy went up from 87 to 91 percent after we cleaned the labels.

  2. Don't report only accuracy here; the classes are very imbalanced.

Common collocations

  • improve accuracy
  • test accuracy
  • high accuracy
  • top-1 accuracy
  • precisionOf all the cases a model marked as positive, the share that really were positive. High precision means few false alarms.
  • recallOf all the cases that really were positive, the share that the model managed to find. High recall means few missed cases.
  • F1 scoreA single number that combines precision and recall by taking their harmonic mean. It is high only when both precision and recall are high.
  • class imbalanceA situation in which some classes in a dataset have far more examples than others, for example 990 normal transactions for every 10 fraudulent ones.

This word in other fields

The same English word can have a different meaning in another field:

More terms: Evaluation and Metrics

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