r - Getting glmnet coefficients at 'best' lambda -


i using following code glmnet: 

> library(glmnet) > fit = glmnet(as.matrix(mtcars[-1]), mtcars[,1]) > plot(fit, xvar='lambda')

enter image description here

however, want print out coefficients @ best lambda, done in ridge regression. see following structure of fit: 

> str(fit) list of 12  $ a0       : named num [1:79] 20.1 21.6 23.2 24.7 26 ...   ..- attr(*, "names")= chr [1:79] "s0" "s1" "s2" "s3" ...  $ beta     :formal class 'dgcmatrix' [package "matrix"] 6 slots   .. ..@       : int [1:561] 0 4 0 4 0 4 0 4 0 4 ...   .. ..@ p       : int [1:80] 0 0 2 4 6 8 10 12 14 16 ...   .. ..@ dim     : int [1:2] 10 79   .. ..@ dimnames:list of 2   .. .. ..$ : chr [1:10] "cyl" "disp" "hp" "drat" ...   .. .. ..$ : chr [1:79] "s0" "s1" "s2" "s3" ...   .. ..@ x       : num [1:561] -0.0119 -0.4578 -0.1448 -0.7006 -0.2659 ...   .. ..@ factors : list()  $ df       : int [1:79] 0 2 2 2 2 2 2 2 2 3 ...  $ dim      : int [1:2] 10 79  $ lambda   : num [1:79] 5.15 4.69 4.27 3.89 3.55 ...  $ dev.ratio: num [1:79] 0 0.129 0.248 0.347 0.429 ...  $ nulldev  : num 1126  $ npasses  : int 1226  $ jerr     : int 0  $ offset   : logi false  $ call     : language glmnet(x = as.matrix(mtcars[-1]), y = mtcars[, 1])  $ nobs     : int 32  - attr(*, "class")= chr [1:2] "elnet" "glmnet"

but not able best lambda , corresponding coefficients. help.

try this:

fit = glmnet(as.matrix(mtcars[-1]), mtcars[,1],      lambda=cv.glmnet(as.matrix(mtcars[-1]), mtcars[,1])$lambda.1se) coef(fit)

or can specify specify lambda value in coef:

fit = glmnet(as.matrix(mtcars[-1]), mtcars[,1]) coef(fit, s = cv.glmnet(as.matrix(mtcars[-1]), mtcars[,1])$lambda.1se)

you need pick "best" lambda, , lambda.1se reasonable, or justifiable, 1 pick. use cv.glmnet(as.matrix(mtcars[-1]), mtcars[,1])$lambda.min or other value of lambda settle upon "best" you.


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