summarize {boost}R Documentation

Summarize the output of classification with boosting functions

Description

Yields text and graphical output that summarizes the misclassifcation error rates that have been achieved with boosting methods

Usage

summarize(boost.out, resp, mout = ncol(boost.out), grafik = TRUE)

Arguments

boost.out An R-object, as obtained from one of the functions 'bagboost', 'logitboost', 'adaboost' or 'l2boost'.
resp A vector containing the class labels of the test instances. Needs to be coded by 0 and 1.
mout The number of boosting iterations for which the error rate shall be printed. Defaults to the number of iterations boosting has been run for.
grafik Logical, indicating whether a plot of the error rates is desired or not.

Value

Just verbatim and graphical output.

Author(s)

Marcel Dettling

References

o
"Boosting for Tumor Classification with Gene Expression Data", Marcel Dettling and Peter B"uhlmann. Bioinformatics (2003), Vol. 19, p. 1061–1069.
o
"BagBoosting for Tumor Classification with Gene Expression Data", Marcel Dettling. To appear in Bioinformatics (2005).
o
Further information is available from the webpage http://stat.ethz.ch/~dettling

See Also

bagboost, logitboost, adaboost, l2boost

Examples

data(leukemia, package = "boost")

## Dividing the leukemia dataset into training and test data
xlearn <- leukemia.x[c(1:20, 34:38),]
ylearn <- leukemia.y[c(1:20, 34:38)]
xtest  <- leukemia.x[21:33,]
ytest  <- leukemia.y[21:33]

## Classification with logitboost
fit <- logitboost(xlearn, ylearn, xtest, presel=50, mfinal=20)
summarize(fit, ytest)

[Package boost version 1.0-0 Index]