View source: R/model_evaluation_plot.r
| model.evaluation.plot | R Documentation | 
Produces plots for model evaluation.
model.evaluation.plot(..., fn.plot = NULL, 
colours=NULL, show.all=FALSE, verbose = 1)
| ... | one or more object of class siamcat-class, can be named | 
| fn.plot | string, filename for the pdf-plot | 
| colours | colour specification for the different siamcat-class-
objects, defaults to  | 
| show.all | boolean, Should the results from repeated cross-validation 
models be plotted? Defaults to  | 
| verbose | control output:  | 
Does not return anything, but produces the model evaluation plot.
The first plot shows the Receiver Operating Characteristic (ROC)-curve, 
the other plot the Precision-recall (PR)-curve for the model. If 
show.all == FALSE (which is the default), a single line representing 
the mean across cross-validation repeats will be plotted, otherwise the 
individual cross-validation repeats will be included as 
lightly shaded lines.
For regression problems, this function will produce a scatter plot between the real and predicted values. If several siamcat-class-objects are supplied, a single plot for each object will be produced.
data(siamcat_example)
# simple working example
model.evaluation.plot(siamcat_example, fn.plot='./eval.pdf')
# plot several named SIAMCAT object
# although we use only one example object here
model.evaluation.plot('Example_1'=siamcat_example,
    'Example_2'=siamcat_example, colours=c('red', 'blue'),
    fn.plot='./eval.pdf')
    
# show indiviudal cross-validation repeats
model.evaluation.plot(siamcat_example, fn.plot='./eval.pdf', show.all=TRUE)
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