I wanted to run SVM (linear, polynomial, and radial kernel) with multiple iterations. I was running this code but was not getting 5 iterations as expected. It was only getting one iteration. Can someone please help? Thanks.
Here is the ode
library(readxl)
data <- read_excel("DATASET", sheet = "ALL2")
View(data)
View(data)
data <- data
str(data)
dim(data)
############### Required Library
install.packages("mlbench")
install.packages("caret")
install.packages("glmnet")
install.packages("psych")
install.packages("tidyverse")
library(caret)
library(glmnet)
library(mlbench)
library(psych)
liberty(tidyverse)
custom <- trainControl(method= "repeatedcv",
number=10,
repeats = 3,
verboseIter = T)
traits = 1
cycles = 5
accuracy_svml = matrix(nrow = cycles, ncol = traits)
model_resample_svml = matrix(nrow = cycles, ncol = traits)
model_R2_svml = matrix(nrow = cycles, ncol = traits)
svml_varImp<- matrix(nrow = cycles, ncol = traits)
for (r in 1:cycles)
{
ind <- createDataPartition(data$Y, p=0.6, list=FALSE)
train <- data[ind,]
test <- data[-ind,]
tunegridsvm = expand.grid(C = c(1:5))
svml <- train(Y ~ .,
data = train,
kernel = "linear",
scale = FALSE)
predicted_test_svml <- predict(svml,test)
accuracy_svml[r,1] <- cor(predicted_test_svml, test$ET, use="complete")
model_resample_svml[r,1] <- RMSE(predicted_test_svml, test$ET)
model_R2_svml[r,1] <- R2(predicted_test_svml, test[,1], form = "traditional")
varImpsvml <- varImp(svml, scale = T)$importance
varImpsvml[,2] <- rownames(varImpsvml)
svml_varImp[[r]]<- list(varImpsvml)
}