Answers ( 2 )

  1. Precision is the ratio of several events you can correctly recall to the total number of events you recall (mix of correct and wrong recalls).
    Precision = (True Positive) / (True Positive + False Positive)

    A recall is the ratio of a number of events you can recall the number of total events.
    Recall = (True Positive) / (True Positive + False Negative)

  2. Precision: Out of the total predicted positives by the model, how many are actually positive.
    Precision = True Positive/ True positive + False positive

    Recall: Out of the total actual positive in the datset, how many positives are correctly predicted by the model

    Recall: True Fositive/ True positive + False Negative

Leave an answer

Browse
Browse