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In Fig. 1 (left panel), mean accuracy ratios for the bins from 1 2 to 4 were.46,.61, and.83.
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Using this formula, enrichment ratios were calculated for the performances of the F1, mean Accuracy, Precision, and Recall decision boundaries.
For example, a square shaped patch needed an area of at least 11 pixels to achieve a mean accuracy of 75%, whilst a linear patch with a width to length ratio of 4 needed an area of 12.3 pixels.
Specific measures like mean prediction power and mean accuracy [92], correct recognition rate (CRR) [85], correct and incorrect diagnosis [84], and SNR and ratio R [88] have also been reported.
The mean accuracy across items (words) was then computed.
The mean accuracy across participants was 0.82 (SD = 0.09).
Percent change in 2-back accuracy was calculated as (mean accuracy on 2-back/4 minus mean accuracy on 2-back/1) divided by mean accuracy on 2-back/1.
Mean accuracy of imputation per individual was higher than mean accuracy per SNP.
Overall classification accuracy was defined as the mean accuracy of all validation steps across subjects.
"Full dataset accuracy" is the estimated mean accuracy on the full dataset of size n.
We performed 500 rounds of bootstrapping and computed mean accuracy and standard deviations of accuracy.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com