ggEnsTrend: Trend of the test accuracies

In classyfire: Robust multivariate classification using highly optimised SVM ensembles

Description

The ggEnsTrend function displays the average test accuracies for every new classifier added to the ensemble, as constructed by the cfBuild function.

Usage

ggEnsTrend(ensObj, xlabel = NULL, ylabel = NULL, showText = FALSE, xlims = NULL, 
            ylims = NULL)

Arguments

ensObj	The R object as generated by cfBuild
xlabel	A sub title for the x axis (optional field).
ylabel	A sub title for the y axis (optional field).
showText	Boolean value, by default set to FALSE. If showText=TRUE, then the values of all test accuracies in the ensemble are displayed in the plot.
xlims	A vector of numeric values that specifies the minimum and maximum values in the x axis.
ylims	A vector of numeric values that specifies the minimum and maximum values in the y axis.

Examples

## Not run: 
data(iris)

irisClass <- iris[,5]
irisData  <- iris[,-5]
            
ens <- cfBuild(irisData, irisClass, bootNum = 100, ensNum = 100, parallel = TRUE, 
               cpus = 4, type = "SOCK")

# Plot the trend of the test accuracies in the ensemble
ggEnsTrend(ens)

# Plot with text 
ggEnsTrend(ens, showText  = TRUE)

# Plot with text; set different limits on y axis 
ggEnsTrend(ens, showText  = TRUE, ylims=c(90, 100))

## End(Not run)

classyfire documentation built on May 29, 2017, 11:05 p.m.