Iris Classification
#install.packages("C50")
#install.packages("tree")
#install.packages("gmodels")
library(C50)
library(tree)
library(gmodels)
iris_setosa <-iris[iris$Species=="setosa",]
iris_versicolor <- iris[iris$Species=="versicolor",]
iris_virginica <- iris[iris$Species=="virginica",]
iris_train<-rbind(iris_setosa[1:25,],iris_versicolor[1:25,],iris_virginica[1:25,])
iris_test <- rbind(iris_setosa[26:50,],iris_versicolor[26:50,],iris_virginica[26:50,])
irisC5.0_train <- C5.0(iris_train[,-5],iris_train$Species)
plot(irisC5.0_train)
#View(iris_train)
mean(iris_train$Species==predict(irisC5.0_train,iris_train))
## [1] 0.9733333
predC5.0_test <- predict(irisC5.0_train,newdata=iris_test)
mean(predC5.0_test==iris_test$Species)
## [1] 0.9466667
CrossTable(iris_test$Species,predC5.0_test)
##
##
## Cell Contents
## |-------------------------|
## | N |
## | Chi-square contribution |
## | N / Row Total |
## | N / Col Total |
## | N / Table Total |
## |-------------------------|
##
##
## Total Observations in Table: 75
##
##
## | predC5.0_test
## iris_test$Species | setosa | versicolor | virginica | Row Total |
## ------------------|------------|------------|------------|------------|
## setosa | 25 | 0 | 0 | 25 |
## | 33.333 | 9.000 | 7.667 | |
## | 1.000 | 0.000 | 0.000 | 0.333 |
## | 1.000 | 0.000 | 0.000 | |
## | 0.333 | 0.000 | 0.000 | |
## ------------------|------------|------------|------------|------------|
## versicolor | 0 | 24 | 1 | 25 |
## | 8.333 | 25.000 | 5.797 | |
## | 0.000 | 0.960 | 0.040 | 0.333 |
## | 0.000 | 0.889 | 0.043 | |
## | 0.000 | 0.320 | 0.013 | |
## ------------------|------------|------------|------------|------------|
## virginica | 0 | 3 | 22 | 25 |
## | 8.333 | 4.000 | 26.797 | |
## | 0.000 | 0.120 | 0.880 | 0.333 |
## | 0.000 | 0.111 | 0.957 | |
## | 0.000 | 0.040 | 0.293 | |
## ------------------|------------|------------|------------|------------|
## Column Total | 25 | 27 | 23 | 75 |
## | 0.333 | 0.360 | 0.307 | |
## ------------------|------------|------------|------------|------------|
##
##
#iris_tree <- tree(Species~.,data=iris_train)