Indeed if a reader were to apply our algorithm, or one like it, with a different goal in mind we advise them to adapt the recall measure to their specific goal.
For the comparison with our study, first, predictions based on expression data only have to be extracted and, subsequently, precision and recall measures need to be calculated using methods similar to those used in our study.
Note that while we predict a sequence of stores (a D-trajectory), the evaluation we provide in the rest of the paper focuses on precision and recall measures (analogous to information retrieval since relevance of ads relies on this more) rather than order (order is considered elsewhere for the shopping mall scenario in [12]).
By combining the SOLNAS in-person recall with the HCHS/SOL telephone recall, we used the 24-hour dietary recall measures closest to the SOLNAS baseline.
Short-term recall measures ask respondents to recall all alcohol that they have consumed during each day in a recent short period (e.g., the last week) (Rehm et al. 1999), based on the assumption that respondents are able to remember consumption more accurately over such short periods.
As such, the current study, through a between groups experimental design, aims to compare the performance of low-knowledge readers on vocabulary and recall measures when they are exposed to glosses providing lexical information versus topic-level information.
We use the recall and precision measures to assess all aligners using simulated datasets, where recall (precision) is calculated by dividing the number of reads that are correctly aligned by the total number of reads (the number of aligned read).
The precision and recall measures are mostly used metric to measure the performance of a classification algorithm.
In addition, we also performed a multivariate one-way MANCOVA for all recall measures with IQ as covariate to compare the recall performance of the three groups separately for each recall measure.
Recall measures the ability of the method to discover the true peaks, whereas precision measures the ability to reject false peaks.
