I have already created my XGBoost classifier in R as in below code
#importing the dataset
XGBoostDataSet_Hr_Admin_8 <- read.csv("CompletedDataImputed_HR_Admin.csv")
#Use factor function to convert categorical data to numerical data
XGBoostDataSet_Hr_Admin_8$Salary = as.numeric(factor(XGBoostDataSet_Hr_Admin_8$Salary, levels =c('L','M', 'H', 'V'), labels =c(1,2,3,4)))
XGBoostDataSet_Hr_Admin_8$Rude_Behavior = as.numeric(factor(XGBoostDataSet_Hr_Admin_8$Rude_Behavior, levels=c('Y', 'M', 'N'), labels =c(1,2,3)))
XGBoostDataSet_Hr_Admin_8$Feeling_undervalued =as.numeric(factor(XGBoostDataSet_Hr_Admin_8$Feeling_undervalued, levels=c('Y', 'M', 'N'), labels =c(1,2,3)))
XGBoostDataSet_Hr_Admin_8$Overall_satisfaction = as.numeric(factor(XGBoostDataSet_Hr_Admin_8$Overall_satisfaction, levels=c('Y', 'M', 'N'), labels =c(1,2,3)))
XGBoostDataSet_Hr_Admin_8$Raises_frozen = as.numeric(factor(XGBoostDataSet_Hr_Admin_8$Raises_frozen, levels=c('Y', 'M', 'N'), labels =c(1,2,3)))
XGBoostDataSet_Hr_Admin_8$Poor_Conditions = as.numeric(factor(XGBoostDataSet_Hr_Admin_8$Poor_Conditions, levels=c('Y', 'M', 'N'), labels =c(1,2,3)))
XGBoostDataSet_Hr_Admin_8$Growth_not_available = as.numeric(factor(XGBoostDataSet_Hr_Admin_8$Growth_not_available, levels=c('Y', 'M', 'N'), labels =c(1,2,3)))
XGBoostDataSet_Hr_Admin_8$Workplace_Conflict = as.numeric(factor(XGBoostDataSet_Hr_Admin_8$Workplace_Conflict, levels=c('Y', 'M', 'N'), labels =c(1,2,3)))
XGBoostDataSet_Hr_Admin_8$Employee_Turnover = as.numeric(factor(XGBoostDataSet_Hr_Admin_8$Employee_Turnover, levels=c('Y', 'N'), labels =c(1,0)))
#split the data in train dataset and test dataset
library(caTools)
split = sample.split(XGBoostDataSet_Hr_Admin_8$Employee_Turnover,SplitRatio = 0.7)
training_set8 = subset(XGBoostDataSet_Hr_Admin_8, split==TRUE)
test_set8 = subset(XGBoostDataSet_Hr_Admin_8, split==FALSE)
#fitting XGBoost to the Training Test
library(xgboost)
classifier9 = xgboost(data = as.matrix(training_set8[-10]), label = training_set8$Employee_Turnover, nrounds = 10)
Now, I need to create a confusion matrix for the XGBoost.
I have searched on the net and unfortunately can't find the solution.
Can anyone please help me out.
Thanks in advance