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Area under the PR curve: Difference between revisions
Created page with "{{see also|Machine learning terms}} ==Introduction== Evaluation of a model's performance in machine learning is essential to determine its capacity for accurately predicting output. One such performance indicator is the area under the Precision-Recall (PR) curve, which measures the tradeoff between precision and recall for different classification thresholds. Machine learning requires the evaluation of a classifier's performance as an essential step in the modeling proc..."
(Created page with "{{see also|Machine learning terms}} ==Introduction== Evaluation of a model's performance in machine learning is essential to determine its capacity for accurately predicting output. One such performance indicator is the area under the Precision-Recall (PR) curve, which measures the tradeoff between precision and recall for different classification thresholds. Machine learning requires the evaluation of a classifier's performance as an essential step in the modeling proc...") |
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