# Tagged Questions

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### When would I choose Lasso over Elastic Net

What are the scenarios where Lasso is likely to perform better than Elastic Net (out of sample prediction)?
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### Estimators for linear regression when multicollinearity is present

I have a multicollinearity problem is a linear regression model and ridge regression was suggested as a solution. So I have spent quite some time researching different ridge regressors in the ...
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### Feature selection & model with glmnet on Methylation data (p>>N)

I would like to use GLM and Elastic Net to select those relevant features + build a linear regression model (i.e., both prediction and understanding, so it would be better to be left with relatively ...
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### Confusion related to elastic net

I was reading this article related to elastic net. They say that they use elastic net because if we just use Lasso it tends to select only one predictor among the predictors that are highly ...
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### Extracting regularization path from glmnet

Does glmnet provide any mechanisms to extract the regularization path from a final model? I'm using Elastic Nets (and L1) to build a binomial classifier and would like to be able to get the ...
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According to Hastie's paper, the elastic net has two equivalent formulations: $\hat{\beta} = \underset{\beta}{\operatorname{argmin}} \left\{ \sum_{i=1}^N(y_i-\sum_{j=1}^p x_{ij} \beta_j)^2 + ... 1answer 321 views ### Replicate simulation study from a paper and calculate the MSE in R I have implemented a Gibbs Sampler for the Bayesian Elastic Net (BEN) according to this paper on Penalized Regression by Kyung et al. In this paper, they execute a simulation study that has been used ... 1answer 157 views ### What is lambda in an elastic net model (penalized regression)? In the language R there is the possibility to estimate the best$\lambda$for an elastic net model via a cross-validation, having set the value of$\alpha$. However, being$\alpha$defined as ... 0answers 58 views ### Penalized methods for categorical data: combining levels in a factor Penalized models can be used to estimate models where the number of parameters is equal to or even greater than the sample size. This situation can arise in log-linear models of large sparse tables of ... 0answers 200 views ### Coding an adaptive elastic net in Matlab I've coded an adaptive lasso based on Zou 2006 and I'm in the process of figuring out how to implement the adaptive elastic net. The L1 penalization has associated weights$w_j$, proportional to the ... 2answers 146 views ### Are penalized regression techniques greedy algorithms? In other words, is it feasible any of the various penalized regression techniques (such as ridge regression, lasso, and elasticnet) could completely miss the optimal solution for a regression model ... 1answer 451 views ### Stepwise regression vs. elastic net I understand that Stepwise regression analysis has lots of limitations, including the assumption that the predictors are not highly correlated with each other. In fact, this limitation was the most ... 1answer 84 views ### Using standardized Y in Elastic Net I have an Elastic Net model that is selecting a number of variables from X, for prediction of Y. The assumption for Elastic Net is that X is standardized (I'm using Z-Scores), and Y is centered around ... 0answers 160 views ### Calculating R-square for Elastic Net I am trying to do "variable selection" using Elastic Net method (Matlab Lasso function with alpha of 0.5). I have 75 predictors in total (some are correlated with each other, hence using Elastic Net ... 1answer 135 views ### Strange definition of RSS for elastic net in scikit-learn (Python) I've been reading the manual about GLM, specifically the one on the elastic net in this link, and they come up with the following function to minimize:$$\frac{1}{2n}||Xw-y||^2_{2}+\alpha \rho ... 1answer 428 views ### Gradient descent and elastic-net logistic regression I'm currently in the process of trying to understand the paper Regularization Paths for Generalized Linear Models via Coordinate Descent by Friedman et al. with regard to the regularization of ... 0answers 339 views ### Post processing random forests using regularised regression: what about bias? I have been playing around with post processing the results of the random forest for regression machine learning algorithm in order to try and do better than the default mean of all trees prediction. ... 2answers 478 views ### Model stability when dealing with large$p$, small$n\$ problem

Intro: I have a dataset with a classical "large p, small n problem". The number available samples n=150 while the number of possible predictors p=400. The outcome is a continuous variable. I want ...
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### Open source implementation elastic net in C or C++

Can anyone provide or point me to a freely available implemention of Elastic Net in C or C++?
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### How to select the final model with elastic net feature selection, cross validation and SVM?

I have a dataset of some 100 samples, each with >10,000 features, some of which highly correlated. Here's what I am doing currently. Split the data set into three folds. For each fold, 2.1 Run ...
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### Cross validation with two parameters: elastic net case

I want to know the cross validation procedure to find the two parameters of elastic net presented by Zou and Hastie on the prostate dataset as example. I can't improve the error rate lasso with k-fold ...
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### Coordinate descent for binomial decision in elastic net for logistic regression

I'm looking to implement a coordinate descent solution to the Elastic Net (Friedman et al, 'Regularization paths for generalized linear models via coordinate descent') for logistic regression. The ...
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### How is the intercept computed in GLMnet?

I've been implementing the GLMNET version of elastic net for linear regression with another software than R. I compared my results with the R function glmnet in lasso mode on diabetes data. The ...