Questions tagged [elastic-net]

A regularization method for regression models that combines the penalties of lasso and of ridge regression.

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Is there any value in models that have a larger out of sample RMSE than a standard deviation?

I am predicting y values from x values using various regression models, elastic net and partial least squares regression (PLSR). To quantify performance of models we utilize root mean squared error (...
1 vote
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Assessing Random Search Cross Validation: Tuning in ElasticNet with Large Feature Sets

I'm working on estimating an ElasticNet model for a large dataframe with over 100,000 variables, resulting in a well overidentified scenario. To tune my model, I've set up a grid of hyperparameters (...
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What is the boundary curve for $λ_1$ and $λ_2$ that give at least a 0 component in elastic net?

Define the elastic net estimate: \$ \hat{\beta}^{\lambda_1, \lambda_2} = \arg \min_{\beta \in \mathbb{R}^p} \left( \frac{1}{2n} \| y - X\beta \|_2^2 + \lambda_1 \ \frac{1}{2} \|\beta \|_2^2 + \lambda_2 ...
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Can you store the value of the predicted variable (Y) at each fold and then correlate the predicted values with the actual data?

In particular, imagine to have a set of features (X) that I use to predict a continuos variable (Y). Is it possible to use elastic net, in a cross-validation framework, use it to predict the value of ...
1 vote
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The importance of stationarity for the oracle property of Elastic Net Regression?

I've been on the lookout for a while, but unfortunately, I'm still coming up empty-handed in my search for papers or books that dive into the theoretical derivation or simulation of the impact of non-...
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How to plot/visualize correlation values from two different methods for comparison?

I am working on a project wherein we are comparing two methods used for modeling gene expression: one method is using elastic net and other is using lasso regression. In one method: we see that ...
61 views

Variable selection in multiply imputed data

I have a dataset with approximately 1800 observations and I'm trying to fit a multivariable logistic regression model (250 cases, 1550 controls). There are 19 covariates (mix of continuous, ordinal ...
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How can you constrain the intercept of a glmnet model to be positive?

If I use the lower.limits = 0 argument, it doesn't apply to the intercept for some reason. I can't find any documentation as to why or how to do it. Any ideas? ...
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For variable selection, would a viable alternative to using lasso be to use ridge with a threshold, or is switching to elastic net preferred?

A similar question was asked here Why can't ridge regression provide better interpretability than LASSO?, and the answer suggested that a main difference between lasso and ridge is that a zero ...
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weird lasso prediction when using lambda 1se

I have performed a leave-one out cross-validated prediction using a lasso regression (with both lambda min and lambda 1se). My sample size is 52 and I have a bit more than 20 predictors. While lambda ...
19 views

Statistical analysis to interpret beta effect size for two different elastic net model

I have two elastic net model and I want to compare their coefficient to say if they have any significant beta effect changes across these two models. I thought of using Anova but realized since we don'...
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Proximal operator of Adaptive Elastic Net

I would like to learn how to find the proximal operator of the Adaptive Elastic Net, from DOI: 10.1214/08-AOS625 "ON THE ADAPTIVE ELASTIC-NET WITH A DIVERGING NUMBER OF PARAMETERS" by HUI ...
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How to interpret glmnet coefficients when computed on ln-transformed data

So I'm analyzing data from a paper I found, which includes categorical variables like sex and disease severity as well as lipidomics data. I wanted to try using elastic-net regression to find ...
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95% confidence interval for C-index after running elastic net for a cox model, and how to get net reclassification index

Can someone please show me how to get 95% confidence interval for c-index in the elastic net codes below: ...
154 views

Imbalanced logistic elasticnet regression

I am performing a logistic elastic net regression to assess which variables influence the outcome and evaluate it. I am working with an imbalanced dataset that consists of 50 cases and 1700 controls. ...
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Which standard error of out-of-sample prediction errors is used to select the model one standard error from the minimum?

In this post I established that the standard error of cross-validation prediction error is the standard deviation of prediction error across folds divided by the square root of the number of folds. ...
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What is the standard error of average cross validation error in elastic net or lasso?

I don't have any colleagues who I can ask about this so I must turn to my colleagues on Cross Validated. I am fitting a stacked adaptive elastic net regression and am having some trouble understanding ...
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Coordinate Descent Alternating between LASSO and Ridge

Is there a way to do Coordinate descent but depending on the variable change the method applied to find the coefficient? For example, apply a LASSO constraint to a predefined 3 variables and Ridge to ...
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1 vote
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Can elasticnet ever select a different set of predictors than LASSO for a given lambda? [closed]

Since ridge regression can never penalize coefficients to zero, can elasticnet ever select a different set of predictors than LASSO for a given lambda?
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1 vote
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Best Datasets and Packages for Comparing LASSO, Elastic Net, and Ridge [closed]

I have been recently been working with the MASS, lars, and glmnet packages to study variable ...
1 vote
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Differences in Performance Between in MASS Package lm.ridge() and enet in elasticnet Package

A background: I am currently working with the 'elasticnet' package (elasticnet v.1.3) maintained by Hui Zou. This package was developed to accompany Hui Zou and Trevor Hastie's Statistical Society B ...
1 vote
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Can I do a second pass Elastic Net only including the most significant predictors?

First off, I am new to predictive modeling and I appreciate any advice. BACKGROUND: I am doing a binomial elastic net where n = 54 and p = 89. This model is for predicting drug effects clinically; ...
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Generalize the 1SE rule to elastic net

When you do LASSO or ridge regression, and pick the hyperparameter using cross-validation, the 1SE rule suggest to select not the best CV result but the one with the most penalization that's still ...
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