svm) to two
specified files. One is in the format that the
function 'svm_load_model' of libsvm can read. The other is for
scaling data, containing a data with centers and scales for all variables.
write.svm(object, svm.file, scale.file)
"svm", created by
svm.
This function is useful when SVM models trained in R shall be used in other environments. The SVM model is saved in the standard format of libsvm. The scaling data is written to a separate file because scaling data is 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 colums being formed of the corresponding mean and scale.
Tomomi TAKASHINA (based on 'predict.svm' by David Meyer) mailto:t.takashina@computer.org
attach(iris.df)
## classification mode
# default with factor response:
model <- svm (Species~., data=iris.df)
# export SVM object to file
write.svm(model, svm.file = "iris-classifier.svm", scale.file = "iris-classifier.scale")
# 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("iris-classifier.scale",sep=",")