Hello Sambit. Step1: Create a matrix out of your predictor data, having columns for every predictor, coding 1 for yes and 0 for no. he matrix should have a row for each observation (called pred.mat below) Besides that, you need a vector with the outcome variable for each observation (best if this is a factor with 2 levels) (called out.v below) Step2 Because you are working with categorical variables, don't forget to always use " standardize = FALSE " in any call to the glmnet functions (see the docs) Step3 To see how the predictor coefficients move over different values of your penalization parameter, simply do something like myLognet<-glmnet(x=pred.mat, y=out.v, standardize = FALSE, family="binomial") and then plot(myLognet, xvar= "lambda", label = TRUE) Note: the labels in the plot indicate column numbers in pred.mat Step4 To find the 'best' value of the penalization parameter, use cv.glmnet with the same parameters plus a type (see ?cv.glmnet). Note: if the criterion you want is not provided 'out of the box', it will take you quite a bit of coding, so if you can, take one of the provided ones. Visually, you can select the 'best' value for the penalization parameter from the plot (see ?plot.cv.glmnet), or you can use some numerical argument to find the reasonable extreme value for the criterion.
Really boilerplate, I guess. Good luck. Nick Sabbe -- ping: nick.sa...@ugent.be link: http://biomath.ugent.be wink: A1.056, Coupure Links 653, 9000 Gent ring: 09/264.59.36 -- Do Not Disapprove -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of sambit rath Sent: donderdag 3 februari 2011 10:58 To: r-help@r-project.org Subject: [R] glmnet with binary predictors Hi Everybody! I must start with a declaration that I am a sparse user of R. I am creating a credit scorecard using a dataset which has a variable depicting actual credit history (good/bad) and 41 other variables of yes/no type. The procedure I am asked to follow is to use a penalized logistic procedure for variable selection. I have located the package "glmnet" which gives the complete elasticnet regularization path for logistic models. I want some help in setting up the process. Can someone point out the basic steps? Thanks Sambit ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
