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rclassificationglmnet

How to use glmnet in R for classification problems

I want to use the glmnet in R to do classification problems.

The sample data is as follows:

y,x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11
1,0.766126609,45,2,0.802982129,9120,13,0,6,0,2
0,0.957151019,40,0,0.121876201,2600,4,0,0,0,1
0,0.65818014,38,1,0.085113375,3042,2,1,0,0,0

y is a binary response (0 or 1).

I used the following R code:

prr=cv.glmnet(x,y,family="binomial",type.measure="auc")
yy=predict(prr,newx, s="lambda.min")

However, the predicted yy by glmnet is scattered between [-24,5].

How can I restrict the output value to [0,1] thus I use it to do classification problems?

Solution

  • I have read the manual again and found that type="response" in predict method will produce what I want:

    lassopre2=predict(prr,newx, type="response")

    will output values between [0,1]