library("e1071", lib.loc="/Library/Frameworks/R.framework/Versions/3.4/Resources/library")
setwd("~/Desktop/Machine Learning A-Z/Part 2 - Regression/Section 6 - Polynomial Regression")
dataset = read.csv('Position_Salaries.csv')
View(dataset)
dataset = dataset[, 2:3]
lin_reg=lm(formula = Salary~.,
data=dataset)
summary(lin_reg)
dataset$level2 = dataset$Level^2
dataset$level3 = dataset$Level^3
poly_reg = lm(formula = Salary~.,
data=dataset)
summary(poly_reg)
library(ggplot2)
ggplot() +
geom_point(aes(x=dataset$Level,y=dataset$Salary),
colour = 'red') +
geom_line (aes (x=dataset$Level, y = predict (lin_reg, newdata=dataset)),
colour = 'blue') +
xlab('Level') +
ylab('Salary')
ggplot() +
geom_point(aes(x=dataset$Level,y=dataset$Salary),
colour = 'red') +
geom_line (aes (x=dataset$Level, y = predict (poly_reg, newdata=dataset)),
colour = 'blue') +
xlab('Level') +
ylab('Salary')
dataset$level4 = dataset$Level^4
poly_reg = lm(formula = Salary~.,
data=dataset)
ggplot() +
geom_point(aes(x=dataset$Level,y=dataset$Salary),
colour = 'red') +
geom_line (aes (x=dataset$Level, y = predict (poly_reg, newdata=dataset)),
colour = 'blue') +
xlab('Level') +
ylab('Salary')
y_pred=predict(lin_reg, data.frame(Level=6.5))
y_pred=predict(poly_reg, data.frame(Level=6.5,
Level2=6.5^2,
Level3=6.5^3,
Level4=6.5^4))
y_pred=predict(poly_reg, data.frame(Level=6.5,
level2=6.5^2,
level3=6.5^3,
level4=6.5^4))
