| plineplot {klaR} | R Documentation |
For a given variable the posteriori probabilities of the classes given by a classification method are plotted. The variable need not be used for the actual classifcation.
plineplot(formula, data, method, x, col.wrong = "red",
ylim = c(0, 1), loo = FALSE, mfrow, ...)
formula |
formula of the form groups ~ x1 + x2 + ....
That is, the response is the grouping factor and the right hand side specifies the (non-factor) discriminators. |
data |
Data frame from which variables specified in formula are preferentially to be taken. |
method |
character, name of classification function
(e.g. “lda”). |
x |
variable that should be plotted. See examples. |
col.wrong |
color to use for missclassified objects. |
ylim |
ylim for the plot. |
loo |
logical, whether leave-one-out estimate is used for prediction |
mfrow |
number of rows and columns in the graphics device, see par.
If missing, number of rows equals number of classes, and 1 column. |
... |
further arguments passed to the underlying classification method or plot functions. |
The actual error rate.
Karsten Luebke
library(MASS)
# The name of the variable can be used for x
data(B3)
plineplot(PHASEN ~ ., data = B3, method = "lda",
x = "EWAJW", xlab = "EWAJW")
# The plotted variable need not be in the data
data(iris)
iris2 <- iris[ , c(1,3,5)]
plineplot(Species ~ ., data = iris2, method = "lda",
x = iris[ , 4], xlab = "Petal.Width")