Description Usage Arguments Value Author(s) Examples
View source: R/machinelearning-functions-svm.R
Classification using the support vector machine algorithm.
1 2 | svmClassification(object, assessRes, scores = c("prediction", "all",
"none"), cost, sigma, fcol = "markers", ...)
|
object |
An instance of class |
assessRes |
An instance of class
|
scores |
One of |
cost |
If |
sigma |
If |
fcol |
The feature meta-data containing marker definitions.
Default is |
... |
Additional parameters passed to |
An instance of class "MSnSet"
with
svm
and svm.scores
feature variables storing the
classification results and scores respectively.
Laurent Gatto
1 2 3 4 5 6 7 8 9 10 11 12 13 | library(pRolocdata)
data(dunkley2006)
## reducing parameter search space and iterations
params <- svmOptimisation(dunkley2006, cost = 2^seq(-2,2,2), sigma = 10^seq(-1, 1, 1), times = 3)
params
plot(params)
f1Count(params)
levelPlot(params)
getParams(params)
res <- svmClassification(dunkley2006, params)
getPredictions(res, fcol = "svm")
getPredictions(res, fcol = "svm", t = 0.75)
plot2D(res, fcol = "svm")
|
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