Weighted recall is a new metric to be used in grid result analysis. Based on a REAL column that the user selects from the training data set in the grid creation process, this metric will evaluate the percentage of that chosen metric caught for each class (e.g. % of fraud dollars caught). This is identical in logic to the standard recall metrics, but focuses on the percentage of a REAL variable caught by the model, instead of the percentage of the number of records caught.
Once the column is selected to use in the weighted recall calculation and the grid is submitted, the weighted recall can be found in the grid results table alongside the other model performance metrics. The name of the weighted recall columns in the grid results table will be:
- weighted_recall_*POSITIVE_CLASS*
- weighted_recall_*NEGATIVE_CLASS*
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