R: Compute a linear discriminant analysis on classified cluster...

sjc.grpdisc {sjPlot}

R Documentation

Compute a linear discriminant analysis on classified cluster groups

Description

Computes linear discriminant analysis on classified cluster groups. This function plots a bar graph indicating the goodness of classification for each group.

Usage

sjc.grpdisc(data, groups, groupcount, clss.fit = TRUE, prnt.plot = TRUE)

Arguments

`data`	A data frame with variables that should be used for the cluster analysis.
`groups`	group classification of the cluster analysis that was returned from the `sjc.cluster`-function
`groupcount`	amount of groups (clusters) that should be used. Use `sjc.elbow` to determine the group-count depending on the elbow-criterion.
`clss.fit`	logical, if `TRUE` (default), a vertical line indicating the overall goodness of classification is added to the plot, so one can see whether a certain group is below or above the average classification goodness.
`prnt.plot`	logical, if `TRUE` (default), plots the results as graph. Use `FALSE` if you don't want to plot any graphs. In either case, the ggplot-object will be returned as value.

Value

(Invisibly) returns an object with

data: the used data frame for plotting,
plot: the ggplot object,
accuracy: a vector with the accuracy of classification for each group,
total.accuracy: the total accuracy of group classification.

Examples

# retrieve group classification from hierarchical cluster analysis
# on the mtcars data set (5 groups)
groups <- sjc.cluster(mtcars, 5)

# plot goodness of group classificatoin
sjc.grpdisc(mtcars, groups, 5)

[Package sjPlot version 2.4.1 Index]