pRoloc (version 1.12.4)

nbClassification: nb classification

Description

Classification using the naive Bayes algorithm.

Usage

nbClassification(object, assessRes, scores = c("prediction", "all", "none"), laplace, fcol = "markers", ...)

Arguments

object

An instance of class "MSnSet".

assessRes

An instance of class "GenRegRes", as generated by nbOptimisation.

scores

One of "prediction", "all" or "none" to report the score for the predicted class only, for all cluster or none.

laplace

If assessRes is missing, a laplace must be provided.

fcol

The feature meta-data containing marker definitions. Default is markers.

...

Additional parameters passed to naiveBayes from package e1071.

Value

An instance of class "MSnSet" with nb and nb.scores feature variables storing the classification results and scores respectively.

Examples

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")