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Questions tagged [lasso-regression]

Lasso regression is a form of regression analysis used for variable selection and regularization. Use this tag for programming questions related to Lasso regression only. You can ask statistical questions on Cross Validated instead

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How does glmnet handle NA values?

How does glmnet in the R package 'glmnet' handle NA values? Or can it not tolerate NA values?
theforestecologist
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How to get the intercept from a linear model with lasso (lars R package)

I am having an hard time in getting the model estimated by the R package lars for my data. For example I create a fake dataset x and corresponding values y like this: x = cbind(runif(100),rnorm(100)) colnames(x) = c("a","b") y = 0.5 + 3 * x[,1,drop…
lucacerone
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Lasso r code - what is wrong with it?

I am attempting to carry out lasso regression using the lars package but can not seem to get the lars bit to work. I have inputted code: diabetes<-read.table("diabetes.txt", header=TRUE) diabetes library(lars) diabetes.lasso = lars(diabetes$x,…
math11
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Tuning a LASSO model and predicting using tidymodels

I want to perform penalty selection for the LASSO algorithm and predict outcomes using tidymodels. I will use the Boston housing dataset to illustrate the problem. library(tidymodels) library(tidyverse) library(mlbench) data("BostonHousing") dt <-…
Augustin
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Calculating the ridge parameter for given ridge estimates

Suppose response and covariate data are below: (1.4, 0.0), (1.4, -2.0), (0.8, 0.0), (0.4,2.0). I want to find the ridge parameter k, for which the ridge estimates are (1, -1/8) by applying the penalty parameter to slope.
Emma Johnsons
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Why grpreg library and gglasso library in R are giving different results for group LASSO?

I have been trying to do unsupervised feature selection using LASSO (by removing class column). The dataset includes categorical (factor) and continuous (numeric) variables. Here is the link. I built a design matrix using model.matrix() which…
Mehmet Yildirim
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glmnet error (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")

I am running the following (truncated) code using glmnet in R # do a lot of things to create the design matrix called x.design > glmnet(x.design, y, thresh=1e-11) where x.design is a n x p design matrix where n > p and y is a n x 1 vector of…
NM_
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Difference between rqPen and quantreg packages in R

I am building a quantile regression model + LASSO penalization for the boston housing data in R. I found 2 packages that can build this kind of models: rqPen and quantreg. rqPen implements a cross validation process to tune the LASSO parameter…
Álvaro Méndez Civieta
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Why calculating MSE in lasso regression gives different outputs?

I am trying to run different regression models on the Prostate cancer data from the lasso2 package. When I use Lasso, I saw two different methods to calculate the mean square error. But they do give me quite different results, so I would want to…
chogall
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Panel Lasso Estimation in R

I have many continuous independent variables and a dependent dummy variable in my data set about individuals in given years. I want to perform feature selection using Logistic Random Effects Lasso/Logistic Fixed Effects Lasso. However, the default…
Luuk van Gasteren
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Nested resampling + LASSO (regr.cvglment) using mlr

I am trying to conduct nested resampling with 10 CVs for the inner and 10 CVs for the outer loop using regr.cvglment. Mlr provides the code using a wrapper function (https://mlr-org.github.io/mlr/articles/tutorial/devel/nested_resampling.html) Now,…
Sarah
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Plotting lasso beta coefficients

I wrote this lasso code in R, and I got some beta values: #Lasso library(MASS) library(glmnet) Boston=na.omit(Boston) x=model.matrix(crim~.,Boston)[,-1] rownames(x)=c() y=as.matrix(Boston$crim) lasso.mod =glmnet(x,y, alpha =1, lambda =…
Majk
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Scoring Metric for scikit-learn's LassoCV

I'm using scikit-learn's LassoCV function. During cross-validation, what scoring metric is being used by default? I would like cross-validation to be based on "Mean squared error regression loss". Can one use this metric with LassoCV? One can…
Oliver Angelil
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How to plot ROC-curve in sklearn for LASSO method?

I want to compare lasso with other classifiers in sklearn. I have a binary outcome vector y. I usually compute a vector probas that contains the predicted probability for each input point to have 1 as a phenotype and then generate a ROC curve fro…
Fringant
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Implementing lasso regression using TensorFlow

I want to run Lasso regression using TensorFlow. As the Lasso regression is simply adding L1-norm to the cost, I am going to define my cost term as cost = RSS + tf.nn.l1_norm(Weight) or cost = RSS + tf.reduce_sum(tf.abs(Weight)) train =…
emerson
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