nbClassification {pRoloc} | R Documentation |
Classification using the naive Bayes algorithm.
nbClassification(object, assessRes, scores = c("prediction", "all", "none"), laplace, fcol = "markers", ...)
object |
An instance of class |
assessRes |
An instance of class
|
scores |
One of |
laplace |
If |
fcol |
The feature meta-data containing marker definitions.
Default is |
... |
Additional parameters passed to
|
An instance of class "MSnSet"
with
nb
and nb.scores
feature variables storing the
classification results and scores respectively.
Laurent Gatto
library(pRolocdata) data(dunkley2006) ## reducing parameter search space and iterations params <- nbOptimisation(dunkley2006, laplace = c(0, 5), times = 3) params plot(params) f1Count(params) levelPlot(params) getParams(params) res <- nbClassification(dunkley2006, params) getPredictions(res, fcol = "naiveBayes") getPredictions(res, fcol = "naiveBayes", t = 1) plot2D(res, fcol = "naiveBayes")