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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