Tagged Questions

2
votes
2answers
116 views

Using LASSO from lars (or glmnet) package in R for variable selection

Sorry if this question comes across a little basic. I am looking to use LASSO variable selection for a multiple linear regression model in R. I have 15 predictors, one of which is categorical(will ...
3
votes
0answers
63 views

How does LASSO select among collinear predictors?

I'm looking for an intuitive answer why a GLM LASSO model selects a specific predictor out of a group of highly correlated ones, and why it does so differently then the best subset feature selection. ...
3
votes
1answer
126 views

LASSO vs forward selection

I have two questions: I use cross validation to select a LASSO model, does the step in which a particular variable enter, indicate its relative importance? Let's age enter in step 1 and sex enter in ...
2
votes
0answers
114 views

LASSO vs AIC for feature selection with the Cox model

I have some questions about the Lasso. After using the AIC or BIC to select a model, the model is fit with the variables selected in order to get the standard errors of the estimates with CIs, ...
1
vote
0answers
261 views

How to select the best variables by RandomForest in R?

I have a table of mRNA levels of my target gene and it's transcription factors in many different condition. What I want to do is to select the most important ...
1
vote
0answers
104 views

Bootstrap randomized Lasso selection for a Cox model

I'm interested in variable selection for a cox proportional hazards model. I've read this article which slightly favours randomized bootstrap lasso selection over bootstrap lasso selection since it ...
1
vote
0answers
115 views

Kernel in PenalizedSVM R package

There is not option to select kernel in penalizedSVM R package. What kernel do they use? Is there some other R package with penalized SVM methods where I can choose various kernels?
5
votes
1answer
274 views

If p > n, the lasso selects at most n variables

One of the motivations for the elastic net was the following limitation of LASSO: "In the p > n case, the lasso selects at most n variables before it saturates, because of the nature of the convex ...
3
votes
0answers
121 views

Variable Selection One by One vs Simultaneously

The high dimensional variable selection problem is really popular now. But I have a question: If I do simple linear regression regressing one response variable on 1 covariate at a time first and then ...
4
votes
1answer
320 views

Variable selection with LASSO

I am trying to fit a predictive gene-based model in survival analysis. My question is: Can I use LASSO as a variable selection method, and then run a multivariate Cox regression to get the ...
3
votes
0answers
237 views

When does LASSO select correlated predictors?

I'm using the package 'lars' in R with the following code: ...
14
votes
3answers
1k views

What are disadvantages of using the lasso for variable selection for regression?

From what I know, using lasso for variable selection handles the problem of correlated inputs. Also, since it is equivalent to Least Angle Regression, it is not slow computationally. However, many ...
8
votes
3answers
2k views

How to apply LASSO to IRLS (logistic regression)?

I have programmed a logistic regression using the IRLS algorithm. I would like to apply a LASSO penalization in order to automatically select the right features. At each iteration, the following is ...
8
votes
2answers
1k views

Soft-thresholding vs. Lasso penalization

I am trying to summarize what I understood so far in penalized multivariate analysis with high-dimensional data sets, and I still struggle through getting a proper definition of soft-thresholding vs. ...