3
votes
2answers
49 views

Advice for interpolating a model

I'm new in Stack Exchange, so I hope no to be off topic. I'm also new in bioinformatics and I was asked to perform an analysis. Briefly, I have a dataset of 29 cell lines and the IC50 values of a test ...
3
votes
1answer
55 views

Interpreting the lasso coefficients

I have used lasso logistic regression on some data and I have some non zero coefficients for some of the features. I want to know based upon the coefficient values how do I rank the features?
16
votes
4answers
431 views

When wouldn't I use LASSO for model selection?

Assume that you need to build a linear model to make predictions for new observations, and that there is uncertainty about which subset of variables should be included in the model. You are only ...
0
votes
0answers
13 views

Why the maxStages argument in biglars.fit does not work

Why doesn't the biglars.fit function work when maxStages is specified? I've tried multiple values and multiple ways of casting $y$ but it doesn't work. ...
2
votes
0answers
27 views

Lasso-ing the order of a lag?

Suppose I have longitudinal data of the form $\mathbf Y = (Y_1, \ldots, Y_J) \sim \mathcal N(\mu, \Sigma)$ (I have multiple observations, this is just the form of a single one). I'm interested in ...
12
votes
2answers
395 views

Why does the Lasso provide Variable Selection?

I've been reading Elements of Statistical Learning, and I would like to know why the Lasso provides variable selection and ridge regression doesn't. Both methods minimize the residual sum of squares ...
3
votes
0answers
118 views

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)?
2
votes
2answers
75 views

What if Lasso selects transformed terms but not untransformed terms

Suppose I have standard normal features $X_i \in \{X_i : i \in \{1,...,1000\}\}$. I extend this set of predictors with transformations as follows: $\{X_i,X_i^2,X_iI(X_i > 0) : i \in ...
2
votes
2answers
144 views

Variable selection with groups of predictors that are highly correlated

What variable selection approach should I consider if I have thousands of predictors with clusters that are extremely correlated? For example I might have a predictor set $X:= ...
0
votes
1answer
92 views

How Can I use some variables selected by LASSO?

I am very new about statistics. So, please understand if my question is somewhat awkward, and please give me related any advice. I have some data set. X = 500 x 100 (500 observations x 100 ...
0
votes
0answers
39 views

Network/structure learning

Given a data set $\mathbf{X}\in\mathbb{R}^{n\times p}$, where $n$ is the number of samples (observations) and $p$ is the number of features, I would like to know what kind of methods exist for ...
0
votes
0answers
59 views

LASSO method: prediction for multi-dimentional reponses

I have a feature matrix, that is 'X' 2000 (observation) x 200 (variable). I also have a response matrix, that is 'Y' 2000 (response) x 2 (variable). I would like to apply LASSO method to the data ...
1
vote
1answer
163 views

Implement Forward, Backward, Step and LASSO in VB .NET

My client wants me to implement Variable selection methods i.e. Forward, Backward, Step and LASSO in VB .Net platform including p-value and AIC. I have no idea about the steps involved to calculate ...
1
vote
0answers
65 views

Feature selection using correlation

I am trying to do some feature selection using correlation. However, I found that my features are not that correlated. The highest correlation was 0.08. So I am not sure if this is a useful thing to ...
1
vote
1answer
104 views

How to check the features which are selected by LASSO

I am using LASSO (glmnet) to do feature selection. However, how can I check which features are selected?
3
votes
4answers
4k 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
133 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
260 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
197 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
390 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
190 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 ...
2
votes
0answers
194 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?
6
votes
1answer
485 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 ...
4
votes
0answers
151 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
574 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
378 views

When does LASSO select correlated predictors?

I'm using the package 'lars' in R with the following code: ...
15
votes
3answers
3k 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. ...