Dear all,
I have a question about using categorical predictors for SVM, using
"svm" from library(e1071). If I have multiple categorical predictors,
should they just be included as factors? Take a simple artificial data
example:
x1<-rnorm(500)
x2<-rnorm(500)
#Categorical Predictor 1, with 5 level
Dear all,
I have a question about using categorical predictors for SVM, using "svm"
from library(e1071). If I have multiple categorical predictors, should they
just be included as factors? Take a simple artificial data example:
x1<-rnorm(500)
x2<-rnorm(500)
#Categorical Predictor 1, with 5 level
Dear all,
I have a question about using categorical predictors for SVM, using "svm"
from library(e1071). If I have multiple categorical predictors, should they
just be included as factors? Take a simple artificial data example:
x1<-rnorm(500)
x2<-rnorm(500)
#Categorical Predictor 1, with 5 level
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