Description Usage Arguments Author(s) See Also Examples
For categorical models, this function generates a graphical representation of the
true vs predicted contingency matrix across classes for a given alpha
.
1 2 3 4 | plotContingency(x, alpha.index=NULL, xlab="class (true)", ylab="class (predicted)",
cex.lab=0.95, main=NULL, col.main="black", cex.main=0.85, cex.axis=1,
symbol.size.inches=0.5, bg.color="steelblue2", fg.color=NULL, margin=0.2,
frequency.label=TRUE, frequency.label.cex=1, frequency.label.offset=0, ...)
|
x |
|
alpha.index |
Integer indices to select alpha values. Default is |
xlab |
Custom x-axis label. |
ylab |
Custom y-axis label. |
cex.lab |
Axis label size. |
main |
Custom title. |
col.main |
Title color. |
cex.main |
Title size. |
cex.axis |
Axis size. |
symbol.size.inches |
Symbol size. |
bg.color |
Symbol color. |
fg.color |
Color of symbol background. |
margin |
Margin size to accomodate symbols. |
frequency.label |
Logical to display class frequency labels. Default is |
frequency.label.cex |
Size of class frequency labels. |
frequency.label.offset |
Offset of class frequency labels. |
... |
Additional plotting parameters. |
Julian Candia and John S. Tsang
Maintainer: Julian Candia julian.candia@nih.gov
1 2 3 4 5 6 7 | data(QuickStartEx)
binarized=rep("low",length(QuickStartEx$response))
binarized[QuickStartEx$response>median(QuickStartEx$response)]="high"
fit = eNetXplorer(x=QuickStartEx$predictor,y=binarized,family="binomial",n_run=20,
n_perm_null=10,seed=111)
plot(x=fit,plot.type="contingency")
plotContingency(x=fit,alpha.index=6)
|
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