glmnet is an R package for Lasso and elastic-net regularized generalized linear models.
My training dataset has about 200,000 records and I have 500 features. (These are sales data from a retail org). Most of …
r foreach parallel-processing glmnetI have a regression model with binary outcome. I fitted the model with glmnet and got the selected variables and …
r statistics regression glm glmnetI am performing lasso regression in R using glmnet package: fit.lasso <- glmnet(x,y) plot(fit.lasso,…
r linear-regression glmnet lasso-regressionI am using glmnet to predict probabilities based on a set of 5 features using the following code. I need the …
r machine-learning glm glmnetconsider the following example rm(list = ls(all=T)) library(ISLR) library(glmnet) Hitters=na.omit(Hitters) # Binary proble - …
r logistic-regression glmnetI have an x-matrix of 8 columns. I want to run glmnet to do a lasso regression. I know I need …
r formula interaction glmnetI am learning the use of glmnet and brnn packages. Consider the following code: library(RODBC) library(brnn) library(glmnet) …
r glmnetHow does glmnet in the R package 'glmnet' handle NA values? Or can it not tolerate NA values?
r na glmnet lasso-regressionIn my dataset I have a number of continuous and dummy variables. For analysis with glmnet, I want the continuous …
r dataset machine-learning glmnetI am trying to run different regression models on the Prostate cancer data from the lasso2 package. When I use …
r machine-learning glmnet lasso-regression mean-square-error