Plot showing the classification of observations based on
classification methods (e.g. lda, qda) for two variables.
Moreover, the classification borders are displayed and the apparent error rates are given in each title.
drawparti(grouping, x, y, method = "lda", prec = 100, xlab = NULL,
ylab = NULL, col.correct = "black", col.wrong = "red",
col.mean = "black", col.contour = "darkgrey",
gs = as.character(grouping), pch.mean = 19, cex.mean = 1.3,
print.err = 0.7, legend.err = FALSE, legend.bg = "white",
imageplot = TRUE, image.colors = cm.colors(nc),
plot.control = list(), ...)
factor specifying the class for each observation.
first explanatory vector.
second explanatory vector.
the method the classification is based on, currently supported are:
lda, qda, rpart, naiveBayes,
rda, sknn and svmlight
.
precision used to draw the classification borders (the higher the more precise; default: 100).
a title for the x axis.
a title for the y axis.
color for correct classified objects.
color for wrong classified objects.
color for class means (only for methods lda and qda).
color of the contour lines (if imageplot = FALSE).
group symbol (plot character), must have the same length as grouping.
plot character for class means (only for methods lda and qda).
character expansion for class means (only for methods lda and qda).
character expansion for text specifying the apparent error rate.
If print.err = 0, nothing is printed.
logical; whether to plot the apparent error rate above the plot (if FALSE),
or into a legend into the upper right corner of the plot (if TRUE).
This argument is ignored, if print.err = 0, i.e. if no error rate is printed.
Backgound colour to use for the legend.
colors used for the imageplot, if TRUE.
A list containing further arguments passed to the underlying plot functions.
Further arguments passed to the classification method.
Karsten Luebke, karsten.luebke@fom.de, Uwe Ligges, Irina Czogiel
partimat