Type parameter of the predict() function

Question

What is the difference between type=\"class\" and type=\"response\" in the predict function?

For instance between:

Answer 1

see ?predict.lm: predict.lm produces a vector of predictions or a matrix of predictions and bounds with column names fit, lwr, and upr if interval is set. For type = "terms" this is a matrix with a column per term and may have an attribute "constant".

> d <- data.frame(x1=1:10,x2=rep(1:5,each=2),y=1:10+rnorm(10)+rep(1:5,each=2))
> l <- lm(y~x1+x2,d)
> predict(l)
        1         2         3         4         5         6         7         8         9        10 
 2.254772  3.811761  4.959634  6.516623  7.664497  9.221486 10.369359 11.926348 13.074222 14.631211 

> predict(l,type="terms")
           x1         x2
1  -7.0064511  0.8182315
2  -5.4494620  0.8182315
3  -3.8924728  0.4091157
4  -2.3354837  0.4091157
5  -0.7784946  0.0000000
6   0.7784946  0.0000000
7   2.3354837 -0.4091157
8   3.8924728 -0.4091157
9   5.4494620 -0.8182315
10  7.0064511 -0.8182315
attr(,"constant")
[1] 8.442991

i.e. predict(l) is the row sums of predict(l,type="terms") + the constant

Answer 2

Response gives you the numerical result while class gives you the label assigned to that value.

Response lets you to determine your threshold. For instance,

glm.fit = glm(Direction~., data=data, family = binomial, subset = train)
glm.probs = predict(glm.fit, test, type = "response")

In glm.probs we have some numerical values between 0 and 1. Now we can determine the threshold value, let's say 0.6. Direction has two possible outcomes, up or down.

glm.pred = rep("Down",length(test))
glm.pred[glm.probs>.6] = "Up"

Answer 3

type = "response" is used in glm models and type = "class" is used in rpart models(CART). See:

• predict.glm
• predict.rpart