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Artificial Intelligence & Machine Learning vocabulary · Evaluation and Metrics

Confusion matrix

Meaning in artificial intelligence & machine learning, with examples

nounCommon term

In artificial intelligence & machine learning, confusion matrix means: A table that shows, for each true class, how many examples the model assigned to each class, so you can see at a glance which classes it mixes up.

In Turkish: karışıklık matrisi, hata matrisi

How it is used

For two classes it has four cells: true positives, false positives, true negatives and false negatives. Precision and recall are calculated from these counts. Teams plot it as a heatmap and look at it in almost every model review.

Example sentences

  1. The confusion matrix shows that the model often mixes up wolves and huskies.

  2. Can you add a confusion matrix for each language to the report?

Common collocations

  • plot a confusion matrix
  • normalized confusion matrix
  • false positives
  • false negatives
  • 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.
  • classificationA task in which a model puts each input into one of a fixed set of categories, for example deciding whether an email is spam or which product category a photo shows.
  • accuracyThe 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.

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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