write.wsvm: Write WSVM Object to File

Description

This function exports an WSVM object (trained by wsvm) to three specified files. One is in the format that the function 'svm_load_model' of libsvm can read, this dataset does NOT contain weight since the original libsvm does NOT support subject weighted svm. The second is for scaling data, containing a data with centers and scales for all variables. The last is the weights for all subjects.

Usage

write.wsvm(object, svm.file = "Rdata.svm", scale.file = "Rdata.scale",
              yscale.file = "Rdata.yscale", weight.file = "Weight")

Arguments

object

Object of class "wsvm", created by wsvm.

svm.file

filename to export the wsvm object to.

scale.file

filename to export the scaling data of the explanatory variables to.

yscale.file

filename to export the scaling data of the dependent variable to, if any.

weight.file

filename to export the weights info.

Value

None

Details

This function is NOT useful since the libsvm do not support subject weighted SVM. But maybe you can use if for the modified version https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#weights_for_data_instances. The SVM model is saved in the standard format of libsvm. The scaling data are written to separate files because scaling data are not included in the standard format of libsvm. The format of the scaling data file is a n times 2 matrix: the n-th row corresponds to the n-th dimension of the data, the columns being formed of the corresponding mean and scale. If scaling information for the dependent variable exists (in case of regression models), it is stored in yet another file (1 times 2 matrix). The weight data just contains all weights.

Examples

Run this code

# NOT RUN {
data(iris)
attach(iris)

## classification mode
# default with factor response:
model <- wsvm(Species ~ ., weight = rep(1,150), data = iris)

# export WSVM object to (temporary) files
svm_file <- tempfile()
scale_file <- tempfile()
weight_file <- tempfile()

write.wsvm(model, svm.file = svm_file, scale.file = scale_file, weight = weight_file)

# read scale file
# the n-th row is corresponding to n-th dimension. The 1st column contains the
# center value, the 2nd column is the scale value.
read.table(scale_file)

# clean up
unlink(svm_file)
unlink(scale_file)
unlink(weight_file)
# }