ML-RV

input <- mtcars[,c("mpg","disp","hp","wt")]
print(head(input))

model <- lm(mpg~disp+hp+wt, data = input)

a <- coef(model)[1]
print(a)

Xdisp <- coef(model)[2]
Xhp <- coef(model)[3]
Xwt <- coef(model)[4]
print(Xdisp)
print(Xhp)
print(Xwt)


Create Equation for Regression Model

Based on the above intercept and coefficient values, we create the mathematical equation.
Y = a+Xdisp.x1+Xhp.x2+Xwt.x3
or
Y = 37.15+(-0.000937)*x1+(-0.0311)*x2+(-3.8008)*x3

Apply Equation for predicting New Values

We can use the regression equation created above to predict the mileage when a new set of values for
displacement, horse power and weight is provided.

For a car with disp = 221, hp = 102 and wt = 2.91 the predicted mileage is −
Y = 37.15+(-0.000937)*221+(-0.0311)*102+(-3.8008)*2.91 = 22.7104