logistic_regression.R

library(ISLR)
names(Smarket)
summary(Smarket)
?Smarket
pairs(Smarket,col=Smarket$Direction)

glm.fit = glm(Direction~Lag1+Lag2+Lag3+Lag4+Lag5+Volume, 
              data=Smarket, family=binomial)
summary(glm.fit)
glm.probs=predict(glm.fit,type="response")
glm.probs[1:5]
glm.pred=ifelse(glm.probs>0.5,"Up","Down")
attach(Smarket)
table(glm.pred,Direction)
mean(glm.pred==Direction)

# make train and test sets
train = Year<2005
glm.fit = glm(Direction~Lag1+Lag2+Lag3+Lag4+Lag5+Volume, 
              data=Smarket, family=binomial,subset=train)
glm.probs=predict(glm.fit, newdata=Smarket[!train,], type="response")
glm.pred=ifelse(glm.probs>0.5,"Up","Down")
Direction.test = Smarket$Direction[!train]
table(glm.pred,Direction.test)
mean(glm.pred==Direction.test)

# fit a smaller model to avoid overfitting
glm.fit = glm(Direction~Lag1+Lag2, 
              data=Smarket, family=binomial,subset=train)
glm.probs=predict(glm.fit, newdata=Smarket[!train,], type="response")
glm.pred=ifelse(glm.probs>0.5,"Up","Down")
Direction.test = Smarket$Direction[!train]
table(glm.pred,Direction.test)
mean(glm.pred==Direction.test)
summary(glm.fit)