Description Usage Arguments Details Value Author(s) See Also Examples
Functions to plot the performance of selectors and compare them to others.
1 2 | perfScatterPlot(metric, modelx, modely, datax, datay=datax,
addCostsx=NULL, addCostsy=NULL, pargs=NULL, ...)
|
metric |
the metric used to evaluate the model. Can be one of
|
modelx |
the algorithm selection model to be plotted on the x axis. Can
be either a model returned by one of the model-building functions or a
function that returns predictions such as |
modely |
the algorithm selection model to be plotted on the y axis. Can
be either a model returned by one of the model-building functions or a
function that returns predictions such as |
datax |
the data used to evaluate |
datay |
the data used to evaluate |
addCostsx |
whether to add feature costs for |
addCostsy |
whether to add feature costs for |
pargs |
any arguments to be passed to |
... |
any additional arguments to be passed to the metrics. For example
the penalisation factor for |
perfScatterPlot
creates a scatter plot that compares the performances of
two algorithm selectors. It plots the performance on each instance in the data
set for modelx
on the x axis versus modely
on the y axis. In
addition, a diagonal line is drawn to denote the line of equal performance for
both selectors.
A ggplot
object.
Lars Kotthoff
misclassificationPenalties
, parscores
, successes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | if(Sys.getenv("RUN_EXPENSIVE") == "true") {
data(satsolvers)
folds = cvFolds(satsolvers)
model = classify(classifier=makeLearner("classif.J48"), data=folds)
# Simple plot to compare our selector to the single best in terms of PAR10 score
library(ggplot2)
perfScatterPlot(parscores,
model, singleBest,
folds, satsolvers) +
scale_x_log10() + scale_y_log10() +
xlab("J48") + ylab("single best")
# additional aesthetics for points
perfScatterPlot(parscores,
model, singleBest,
folds, satsolvers,
pargs=aes(colour = scorex)) +
scale_x_log10() + scale_y_log10() +
xlab("J48") + ylab("single best")
}
|
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