Glossary:R-Metric
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- R-Metric (Recall Metric)
- absolute measure of performance of two spaced repetition algorithms based on their ability to predict recall before a grade is scored. As of SuperMemo 18, R-Metric is used solely to compare Algorithm SM-15 (known from SuperMemo 16) and the new Algorithm SM-18. It is shown as percentage in Statistics and Toolkit : Statistics : Analysis : Use : Efficiency : R-Metric. R-Metric is a difference between the performance of the two algorithms:
R-Metric=LSRM(Alg-15)-LSRM(Alg-18)
, whereLSRM
is the least squares predicted recall measure for a given algorithm. R-Metric greater than zero shows superiority of Algorithm SM-18. R-Metric less than zero indicates underperformance of the new algorithm.LSRM
is a square root of the average of squared absolute differences in recall predictions:abs(Recall-PredictedRecall)
, whereRecall
is 0 for failing grades andRecall
is 1 for passing grades.PredictedRecall
is a prediction issued by the algorithm before the repetition. In Algorithm SM-18, the prediction is a weighted average of the value taken from the Recall[] matrix, and R (retrievability) computed from S (stability) and the used interval. The weight used is based on prior repetition cases which inform of the significance of the Recall[] matrix prediction (the prediction becomes more meaningful with more prior repetition data)