ROC_ | R Documentation |
[.] Do ROC analysis and plot it's results (ROC_)
ROC_(x, labels, label.ordering = NULL, make_plots = TRUE)
ROC_table(prediction.obj)
ROC_plots(prediction.obj)
labels |
A vector, matrix, list, or data frame containing the true class
labels. Must have the same dimensions as |
label.ordering |
The default ordering (cf.details) of the classes can be changed by supplying a vector containing the negative and the positive class label. |
make_plots |
Logical. If TRUE (default) Sensitivity-Specificity plot and plot of sensitivity and specificity at each cot-off point are plotted. |
prediction.obj |
An object of class |
A) plots as listed in description of make_plots
.
B) Table of performance measures a optimal cut of point.
Vilmantas Gegzna
This function is based on package ROCR.
library(ROCR)
library(spHelper)
data(ROCR.simple)
ROC_(ROCR.simple$predictions, ROCR.simple$labels)
## Compared groups "0 vs. 1"
## Group treated as positive "1"
## AUC "0.83"
## Cut-off "0.5015"
## Sensitivity (True positive rate, Se) "0.85"
## Specificity (True negative rate, Sp) "0.85"
## Mean of Se and Sp "0.85"
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