f: f
In hypergate: Machine Learning of Hyperrectangular Gating Strategies for High-Dimensional Cytometry
f R Documentation
f
Description
Computes the F_beta score given an intenger number of True Positives (TP), True Negatives (TN). It is optimized for speed and n is thus not the total number of events
Usage
f(TP, TN, n, beta2 = 1)
Arguments
TP
Number of true positive events
TN
Number of true negative events
n
beta^2*(TP+FN)+TN+FP
beta2
squared-beta to weight precision (low beta) or recall (high beta) more
hypergate documentation built on Aug. 31, 2023, 5:12 p.m.
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| f | R Documentation |
f
Description
Computes the F_beta score given an intenger number of True Positives (TP), True Negatives (TN). It is optimized for speed and n is thus not the total number of events
Usage
f(TP, TN, n, beta2 = 1)
Arguments
TP |
Number of true positive events |
TN |
Number of true negative events |
n |
beta^2*(TP+FN)+TN+FP |
beta2 |
squared-beta to weight precision (low beta) or recall (high beta) more |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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