Timeline for cv.glmnet vs glmnet
Current License: CC BY-SA 4.0
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| Sep 20, 2022 at 14:32 | comment | added | C C |
Thanks for the reply! However changing the s parameter doesn't seem to resolve the issue When i manually fit a ridge regression model using the minimum lambda value : ridge.fit <- glmnet(model.matrix(Apps~.,College), College$Apps, alpha=0, lambda=cv.ridge$lambda.min) Then predict on the data : pred.out <- predict(ridge.fit, model.matrix(Apps~.,College)) the test MSE is 1359837 which differs from the cv.glmnet way. In the predict call for the ridge model I have also tried specifying the s parameter to lambda.min as well but it has no effect on the result.
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| Sep 20, 2022 at 12:02 | history | edited | cdalitz | CC BY-SA 4.0 |
added 93 characters in body
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| Sep 20, 2022 at 11:57 | history | answered | cdalitz | CC BY-SA 4.0 |