decisionTree

library(RWeka)
library(caret)
library(e1071)
library(rpart)
DB <- read.csv("/home/onu/Desktop/ML/Imtiaz/data.csv")
DB$class <- as.character(DB$class)
DB$class <- as.factor(DB$class)
DB$ind <- sample(2,nrow(DB),replace=TRUE,prob=c(0.7,0.3))
trainData <- DB[(DB$ind == 1),]
testData <- DB[(DB$ind ==2),]
model <- J48(class~age+gender+tB+dB+alkphos+sgpt+sgot+tP+al.B+aG,data=trainData)
model
head(testData)
x_test <- testData[,1:10]
prediction <- predict(model,x_test)
testData1 <- na.omit(testData)
prediction
confusionMatrix(testData$class,prediction)