Questions tagged [elastic-net]
A regularization method for regression models that combines the penalties of lasso and of ridge regression.
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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 ...
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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 ...
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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 ...
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1answer
31 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 ...
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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?...
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What is the correct way to write the elastic net?
I am confused about the correct way to write the elastic net. After reading some research papers there seems to be three forms
1) $\exp\{-\lambda_1|\beta_k|-\lambda_2\beta_k^2\}$
2) $\exp\{-\frac{(\...
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17 views
How train function in caret choose lamda for elastic net
I'm a beginner in elastic net. I'm using following code for elastic net in R
...
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1answer
41 views
Why is Lasso and Ridge not giving better results than OLS?
I am trying to find an example in which Lasso and Ridge regression are doing better than simple OLS.
I am trying to run the Boston example that appears in the MASS library in R. The dependent ...
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26 views
Ridge vs. Lasso vs. Elastic Net [duplicate]
I have a theoretical question. I was reading about ridge regression, lasso and the elastic net, and is very impressed. One thing is not quite clear to me.
I would like to know when should I use each ...
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30 views
How does regularized regression overcome the p > n problem?
So, I understand why simple linear or logistic regression will have infinite solutions in this case (good answers here and here). But while LASSO will only select n features, Elastic net does not have ...
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Outliers and influential observations in elastic net logistic regression
My dataset has many biomarkers and the boxplots of these variables show the presence of many outliers. However, these 'outliers' are real data and not misread observations. I want to use elastic net ...
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Elastic Net - number of non-zero variables
I have a question regarding the interpretation of the trace of coefficients when running Elastic net with the package glmnet in R.
This is the plot I obtain with alpha = 0.5
My understanding is that ...
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2answers
230 views
One-to-one correspondence between penalty parameters of equivalent formulations of penalised regression methods
Ridge, LASSO and Elastic Net are three very popular methods of penalised regressions. All of these have more than one formulations. For example, two formulations for Ridge are:
minimise $\lVert Y - X ...
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23 views
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 ...
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31 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 ...
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46 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 ...
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2answers
134 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 ...
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2answers
496 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 ...
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1answer
49 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 ...
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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 ...
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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 ...
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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 ...
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1answer
35 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 ...
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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 ...
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1answer
250 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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1answer
114 views
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 ...
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1answer
57 views
why does lasso select at most n predictors?
From the seminal paper on elastic net regularization from Zou and Hastie 2005, I read
...
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211 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 ...
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1answer
448 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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47 views
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 ...
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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-...
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0answers
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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, ...
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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, ...
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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 ...
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3answers
236 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 ...
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209 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 ...
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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 ...
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0answers
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How can I use the coefficient and important variables obtained from elastic net modelling [closed]
I have a big question here. Although I search over internet and also in research papers but couldn't find an answer to it.
I ran elastic net over a dataset that had close to 300 variables and a ...
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1answer
211 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?
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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 ...
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1answer
283 views
Sample size calculation for elastic net regression
I am using elastic net regression to investigate the effect of preditors on the response variable while accounting for multicollinearity among the predictors. But I wish to perform a sample size ...
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At a loss regarding feature selection vs coefficient estimation. Can you ever re-do the latter after the former?
I'm looking at a binary classification problem where p>>>n (9,000 gene expression variables for 290 patients who either have or don't have disease).
I hypothesized that it would be easy to find "...
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1answer
283 views
what's the difference between multinomial logistic regression and traditional regression?
Could anyone please explain to me what is the difference between multinomial logistic regression and traditional regression?
I have used a method called elastic-net as the response variables are in ...
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1answer
372 views
Multivariate Elastic Net with glmnet [closed]
I am using glmnet package for elastic net.
I'd like to perform variable selection and classification on a 50x41 data set with 3 response variables (one continuous and two categorical), but I have not ...
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36 views
Do I need to standardize if I don't care about covariate effects? (Elastic Net Regression)
I am using elastic net logistic regression to develop a classification model. I understand that generally we standardize the covariates before fitting any models so that we "penalize fairly" all the ...
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394 views
Soft-thresholding for the LASSO with complex valued data
I'm currently implementing coordinate descent for the LASSO with complex-valued data. For this, one needs a complex version of the soft-thresholding operator, which seems hardly available on the net.
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1answer
677 views
Glmnet: How to select Lambda and Alpha
I'd like to pick the optimal lambda and alpha using the Glmnet package. I'm open to all models (Ridge, Lasso, Elastic). I'm assuming some out of sample error/cross validation is the best model ...
