Commit 832af2a0 authored by Jakob Wirbel's avatar Jakob Wirbel

do not evaluate model.evaluation.plot calls, since it breaks the CI for some reason.

parent de361a64
......@@ -208,33 +208,7 @@ model.evaluation.plot('FR-CRC'=siamcat.fr,
colours=c('dimgrey', 'orange'))
```
```{r eval_plot_hidden, fig.width = 6, fig.asp=1, fig.align="left", echo=FALSE}
args <- list('FR-CRC'=siamcat.fr, 'CN-CRC'=siamcat.cn)
colours=c('dimgrey', 'orange')
plot(NULL, xlim = c(0, 1), ylim = c(0, 1),
xlab = "False positive rate", ylab = "True positive rate",
type = "n")
title(paste("ROC curve for the model", sep = " "))
abline(a = 0, b = 1, lty = 3)
legend.val <- c()
for (i in 1:length(args)) {
legend.val <- c(legend.val,
as.numeric(SIAMCAT:::single.roc.plot(args[[i]], colours[i],
show.all=FALSE, verbose=0)))
}
legend('bottomright',
legend= paste0(names(args),
' AUC: ' ,
format(legend.val, digits=3)),
col=colours, lty=1, lwd=2, cex=0.8, y.intersp=1.5)
```
![](./eval_plot_holdout.png)
# Session Info
......
......@@ -238,10 +238,12 @@ To plot the results of the evaluation, we can use the function
`model.evaluation.plot`, which produces a pdf-file showing the ROC and PR
Curves for the different resamples runs as well as the mean ROC and PR Curve.
```{r eval_plot, fig.height=6, fig.width=6, fig.align='left', message=FALSE}
```{r eval_plot, eval=FALSE}
model.evaluation.plot(siamcat)
```
![](./eval_plot.png)
## Interpretation Plot
The final plot produced by `SIAMCAT` is the model interpretation plot, created
......
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