prediction

View(Admission_Predict)
head(Admission_Predict)
summary(Admission_Predict)
length(Admission_Predict$SOP)
str(Admission_Predict)
total_admitss= sum(Admission_Predict$`Chance of Admit` == 1)/length(Admission_Predict$`Chance of Admit`)
total_admitss
index<- sample(1:nrow(Admission_Predict),size = 0.75*nrow(Admission_Predict))
train.popu = Admission_Predict[index,]
test.popu = Admission_Predict[index,]
head(train.popu)
head(test.popu)
length(train.popu$SOP)
length(test.popu$SOP)
class(CGPA)
class(`University Rating`)
summary(Admission_Predict)
#change class
Admission_Predict<- factor(Admission_Predict)
pairs(Admission_Predict[,2:7])
attach(Admission_Predict)
pairs(`Chance of Admit`~Research+CGPA+LOR+SOP+`University Rating`+`TOEFL Score`+`GRE Score`)
pairs(Admission_Predict)
#pairs(iris[,1:4], col=iris$Species)
sapply(Admission_Predict, sd)
xtabs(~SOP+LOR)
model1<- glm(formula = `Chance of Admit`~ Research+CGPA+LOR+SOP+`University Rating`+`TOEFL Score`+`GRE Score`,data= 'Admission_Predict')
model1
summary(model1)
plot(model21)
plot(model1)