perfCalc: Computes variety of predictor evaluation measures based on...
In BaderLab/netDx: Network-based patient classifier
Description
Usage
Arguments
Value
Examples
Description
Computes variety of predictor evaluation measures based on the confusion
matrix
Usage
1
perfCalc(dat)
Arguments
dat
(data.frame): 5 columns: score, tp, fp, tn, fn.
One row per cutoff
score for feature selection
Value
(list)
stats (data.frame): score, f1, ppv, precision and recall. One row
per cutoff for feature selection
auc (numeric between 0 and 1): AUC of overall ROC curve
prauc (numeric between 0 and 1): AUC of overall precision-recall curve
Examples
1
2
BaderLab/netDx documentation built on Sept. 26, 2021, 9:13 a.m.
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Description Usage Arguments Value Examples
Description
Computes variety of predictor evaluation measures based on the confusion matrix
Usage
1 | perfCalc(dat)
|
Arguments
dat |
(data.frame): 5 columns: score, tp, fp, tn, fn. One row per cutoff score for feature selection |
Value
(list) stats (data.frame): score, f1, ppv, precision and recall. One row per cutoff for feature selection auc (numeric between 0 and 1): AUC of overall ROC curve prauc (numeric between 0 and 1): AUC of overall precision-recall curve
Examples
1 2 |
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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