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Questions tagged [elastic-net]

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

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408 views

Why is Elastic Net called Elastic Net?

What is the etymology of "Elastic Net" in Elastic Net Regularization? Does it have anything to do with the name of "lasso"?
18 views

Elastic Net Regression in R formula

This is not a question of how to do Elastic Net Regression in R, but understanding the objective function of Elastic Net Regression from the glmnet package. From the package itself the objective ...
61 views

Biased prediction (overestimation) for xgboost

I run xgboost and elastic-net on the same dataset for a classification problem, say we have ...
55 views

How to interpret coefficients of a multinomial elastic net (glmnet) regression

I'm trying to model a membership in one of three well-being clusters (flourisher, normative, languisher) based on a set of predictors, using elastic net for both variable selection & modelling. I ...
29 views

Feature Engineering for Multiple Regression

My goal: I want to predict a single output value from multiple inputs, some of which are numerical and some of which are categorical. To do this, I plan on building a multiple-regression model (...
120 views

L1 and L2 regularization showing increased MSE with added vars (that eventually decreases)

I am attempting to run Ridge, LASSO, and Elastic Net regression as the regularization approaches are commonly used in the problem I'm working to solve. I have successfully run both glmnet() and cv....
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Number of Variables in Elastic Net

I have a data set with 1000 observations and 150 independent variables. When I apply elastic net, I end up with 100 variables. I wonder if I need to do any additional feature selection or if I can use ...
10 views

elastic net with random interventions

Since elastic net gets rid of regressors that do not correlate, would it make sense to randomly put in a bunch of interventions (pulses, level shifts, ect)? If the intervention is not needed, won't ...
12 views

Does elastic net with Arima errors make sense?

I know of regression with arima errors, but can one also do elastic net regression with arima errors? I ask because I read somewhere that the residuals for elastic net are not really valid since ...
37 views

Elastic net/LASSO with soft labels

Sometimes you do not have firm Y/N labels, but e.g. 80% probability of Y as a label. E.g. this happens, if you train a model on a small amount of labelled data, predict for a large amount of ...
26 views

Elastic net regression with uneven penalties for predictors

For a regression model where you are certain that y that depends on some predictors but are agnostic about whether some other predictors should enter, how should you incorporate this prior information?...
76 views

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Why does sklearn.linear_model.enet_path give different results than glmnet_python?

The results alpha path from enet_path and the lambda path from ...
33 views

Elastic net chooses lags beyond ACF cutoff

I've been using Elastic net for time series forecasting. I’m using first difference of the series. Normally I use the ACF to determine the number of lags to use. I was curious, if I would produce more ...
61 views

Regularization techniques (ridge, lasso or elastic-net regression) for meta-analysis

I was perusing the StatQuest YouTube channel, and serendipitously listened to a series of videos on regularization techniques (ridge, lasso or elastic-net regression). It came to my mind that such ...
373 views

How to interpret / metric Lasso regression coefficients

Edited Question, since it was a duplicate I used Matlab to make a lasso model for my data that has 41 predictors and 1 response variable, and perhaps I used more variables that I need too or maybe ...
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R glmnet package: why is elasticnet parametrized like that? [duplicate]

The documentation for glmnet in R here states that it solves the following minimization problem: Why did the authors choose to ...
539 views

Showing the Equivalence Between the ${L}_{2}$ Norm Regularized Regression and ${L}_{2}$ Norm Constrained Regression Using KKT

According to the references Book 1, Book 2 and paper. It has been mentioned that there is an equivalence between the regularized regression (Ridge, LASSO and Elastic Net) and their constraint ...
102 views

CrossValidation in ElasticNet Lambda Parameter

Generally, 10-fold CV is used to find the best $\lambda$ (the shrinkage parameter, not the trade-off between L1 and L2 norm $\alpha$ - see https://stats.stackexchange.com/a/64278/185237) in an elastic ...
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Help: Null Values for penalized SVM

I am interested in fitting a SVM model to my data with Elastic SCAD penalty. I was trying to use the penalizedSVM library for this. The issue is that for some reason, the library outputs a null model ...
28 views

Ridge, Lasso or Elastic nets used in Accounting Research

I am trying to come up with ideas for my master's thesis and was wondering why literature on the above mentioned regression methods within Accounting Research is non-existent? I felt like the ...
53 views

Probability that feature selection in elastic net regularisation is meaningful - evaluating the statistical significance of chosen features

I have a research question - can I use baseline clinical features to predict my binary clinical outcome in individual patients? I am interested if the performance of my model is greater than chance. I ...
59 views

Cross-validation with one-standard-rule for Elastic Net

I would like to use one-standard -deviation rule for my hyper-parameter selection for elastic net. I understand how to do it for ridge or lasso, but when it comes to two regularization parameters I am ...
37 views

How to check if covariates in multiple regression is explaining the same?

I am a master's student doing my thesis at the moment and have come to the point of determining my empirical setup. I would like to get some guidance, in terms of what I am thinking is proper.. I ...
16 views

how to scale count data when I use elastic net model

I'm using elastic net model for my prediction. I have 100 features. 30 of them are numeric values (100-999). The rest of predictors are simply counts, ranging from 0 to 10 (most of them are 0-3). For ...
407 views

Interpreting glmnet cox coefficients

There have been similar questions regarding interpretation of glmnet results. However this is more specific to the cox part of the package. I am trying to create a prognostic score for cancer ...
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Is there any two-stage procedure for elastic net as LASSO?

I read this post Why use Lasso estimates over OLS estimates on the Lasso-identified subset of variables? . It says the LASSO shrinkage causes the estimates of the non-zero coefficients to be biased ...
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Confused about hyperparameter selection for elastic net regularization using glmnet

I am following the glmnet tutorial here and confused about the statement: We see that lasso (alpha=1) does about the best here. We also see that the range of ...
68 views

why does lasso select at most n predictors?

From the seminal paper on elastic net regularization from Zou and Hastie 2005, I read ...
252 views

R squared / deviance explained for elastic net glmnet

I am using R glmnet function for the elastic net for logistic regression with binary outcome and would like to calculate the R-square value. I am getting different results when I use the dev.ratio ...
771 views

how to use elastic net to select a set of features

I have a dataset with 500 samples and 100 features. I need to come up with a set of features. The management prefer a model with a smaller set of features. How exactly should I use elastic net to do ...
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Finding the “optimal” non linear relationship between two variables

I am looking for finding associations between a binary outcome regarding women fertility and several potential risk factors. Since this study is quite exploratory, I was planning to include all my ...
49 views

The limitations of Elastic-net regularization [duplicate]

I know that Elastic-net regularization is the combination of L1 and L2 regularization. My question is what are the limitations of Elastic-net regularization? My question is not related to Elastic-...
31 views

Equations of Elastic net regularization [duplicate]

I know that the Elastic net takes care of the limitations of Lasso by adding an L 2 penalty term. In the attached picture has been mentioned that the two formulas are equivalent. I tried to show this, ...
17 views

Scoring System via Elastic Net and Bootstrapping a reasonable approach?

I am still at model Building stage. It's for heart surgery data, Building a scoring System for (near-future) death by a set of variables (~20) on a cohort of about 500 patients, 2 competing therapies, ...
291 views

Feature selection Stability of Elastic net vs Lasso

I am new to regularized regression, and I was told that Elastic net overcomes many issues of the Lasso Regression. Especially, in the case of highly correlated predictors, Lasso variable selections ...
357 views

For high dimensional data, does it make sense to do feature selection before running elastic net?

I have a dataset with $n = 800$ observations and $p = 2000$ features. I'm running elastic net for binary classification. My question is: Does it make sense to do some feature selection to reduce the ...
258 views

How to use Elastic Net Model to Reduce Collinearity

I am using R to perform a linear regression with a dataset that has clearly correlated independent variables (collinearity). I am using the vif (variance inflation factor) function from the car ...
98 views

Elastic Net and collinearity

I am performing elastic net for variable selection on a dataset of 95 records and 41 variables. The response is a continuous numerical. I choose the alpha and lambda parameters through 10 fold cross ...
249 views

Elastic net visualization [closed]

Sorry for the naive question, but is there a way to display in a graph the elastic net (or penalized regression in general) results? Specifically, how can I render the coefficients of the variables?
670 views

How to decide whether to use Ridge Regression/LASSO/Elastic Net or Random Forest for Feature Selection?

My understanding is rudimentary and high level but it seems like Ridge Regression/LASSO/Elastic Net would be better when the data is linear and Random Forest is better when the data is nonlinear? Also ...