Recall (Data Science): Revision history

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4 November 2024

  • curprev 11:5911:59, 4 November 2024‎ 핵톤 talk contribs‎ 2,241 bytes +2,241‎ Created page with "'''Recall''' is a metric used in data science, particularly in classification problems, to measure the completeness of positive predictions. It represents the ratio of true positive predictions to the sum of true positives and false negatives, reflecting the model's ability to identify all relevant instances within the data. ==Definition== Recall is calculated as: :'''Recall = True Positives / (True Positives + False Negatives)''' This metric is crucial when the focus is..." Tag: Visual edit
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