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Accuracy: Difference between revisions
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(Created page with "In machine learning, accuracy refers to the ability to accurately predict the output of a given input. It is a common metric used to evaluate the performance of a model in particular classification tasks. ==Mathematical Definition== The accuracy of a model in a classification task is the sum of all the correct predictions divided by the total number of predictions. It can be expressed mathematically as: Accuracy = Number correct predictions / Total...") |
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The accuracy of a model in a classification task is the sum of all the correct [[prediction]]s divided by the total number of predictions. It can be expressed mathematically as: | The accuracy of a model in a classification task is the sum of all the correct [[prediction]]s divided by the total number of predictions. It can be expressed mathematically as: | ||
Accuracy = Number correct predictions / Total number of predictions | <math>Accuracy = Number correct predictions / Total number of predictions</math> | ||
==Example== | ==Example== | ||