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rpredictglmnet
Veera
Veera

Reputation: 869

How to predict using only weights obtained from glmnet in R?

One can make predictions using predict(fit,newx) method. But how to predict if I don't have the fit object itself but only the weights of the predictors as vector file and new observations for predictors as a matrix file? The predictors and the outcome both are continuous variables.

Upvotes: 0

Views: 552

Answers (1)

thc
thc

Reputation: 9705

You can just use matrix multiplication, which is what glmnet does. In the predict function, it is: as.matrix(cbind2(1, x) %*% coefs)

Example:

library(glmnet)

x=matrix(rnorm(100*20),100,20)
y=rnorm(100)
fit1=glmnet(x,y)
coefs <- coef(fit1,s=0.01) # extract coefficients at a single value of lambda

manaul_pred <- as.matrix(cbind2(1, x) %*% coefs)
pred <- predict(fit1,newx=x,s=0.01)

manual_pred - pred # there is a negligible difference due to numeric precision

Upvotes: 3

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