gcl-package {gcl}R Documentation

GCL: A package for Computing fuzzy rules or tree classifiers from numeric data

Description

gcl is a R (http://www.r-project.org) package for computing fuzzy rules and tree classifiers given numeric input data.

Details

Package: gcl
Type: Package
Version: 1.06.5
License: GPL Version 2
URL: http://www.r-project.org,
http://www.mit.edu/~sav/fuzzy/latest/

Function index:

acc.eval                Function that evaluates the accuracy of a
                        classifier function on a data frame
ci.eval                 Function that evaluates the cindex of a
                        classifier function on a data frame
cindex                  Compute the c-index
cv                      N-fold crossvalidation
cv52                    5x2 fold crossvalidation
cvcomp                  Compare two models using crossvalidation
gain                    Computes information theoretic gain
gainr                   Computes information theoretic gain ratio
gcl                     GCL: a fuzzy rule classifier generator
hanley                  Statistically compare C-indices
loocv                   Leave one out crossvalidation

gcl

This function computes a fuzzy rules classifier given numeric input data as the data frame or matrix mydata.

The algorithm for doing so is described in Vinterbo et al., 2005.

When applied, gcl returns another R function that implements the found classifier. This computed classifier function takes one argument, a vector, matrix or data frame to be classified, and outputs a vector of class memberships for each input vector, matrix or data frame row. (See examples section below).

Even though the paper cited above is on classification using gene expression data, numerical data in general can be used. For instance

> library(gcl)
> library(datasets)
> data(iris)
> classifier <- gcl(iris, nlev=5)
> acc.eval(classifier, iris)
computes a fuzzy rule classifier for Edgar Anderson's Iris Data set and evaluates the classifier accuracy on the same data set.

Availability

The gcl program should be considered as being testing software. It is supplied as is, and NO WARRANTY whatsoever is given.

GCL is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License http://www.gnu.org/copyleft/gpl.html as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

GCL is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with GCL; if not, write to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA

The gzipped tar archive containing the latest gcl R package version can also be gotten here: http://www.mit.edu/~sav/fuzzy/latest/

Author(s)

Staal A. Vinterbo

Maintainer: complain to <staal at dsg fullstop harvard fullstop edu>

References

Vinterbo, S.A.; Kim, E. and Ohno-Machado, L. Small, fuzzy and interpretable gene expression based classifiers. Bioinformatics, 2005, 21, 1964-1970. http://bioinformatics.oxfordjournals.org/cgi/content/abstract/21/9/1964

See Also

gcl

Examples

## run the demo
demo(gcldemo)

## play with the iris data set:
## Not run: 
library(gcl)
library(datasets)
data(iris)
classifier <- gcl(iris, nlev=5)
acc.eval(classifier, iris)
## End(Not run)

## compare performance of gcl and tcl
## Not run: 
library(gcl)
library(datasets)
data(iris)
cv52(iris, gcl, tcl, acc.eval, nlev=5, t.nlev=5)
## End(Not run)

[Package gcl version 1.06.5 Index]