similar to: error in Elastic net

Dear R users, I have problem with extracting coefficients from a object. Here, X (predictor)and Y (response) are two matrix , I am regressing X ( dimensions 10 x 20) on each of columns of Y[,1] (10 x 1) and want to store the coefficient values. I have performed a Elastic Net regression and I want to store the coeffcients in each iteration. I got an error message . I do not

Dear R users, I am using "enet" package in R for applying "elastic net" method. In elastic net, two penalities are applied one is lambda1 for LASSO and lambda2 for ridge ( zou, 2005) penalty. But while running the analysis, I realised tht, I optimised only one lambda. ( even when I looked at the example in R, they used only one penality) So, I am

Hello, I am attempting to use elasticnet to classify a number of documents. The features are words. The data is coded into a matrix with each document as a row and each word as a column. The data is binary, with {0,1} indicating the presence of a word. I want to use the cross validation function of elasticnet (cv.enet). However, when the code selects a random subset of the data for a given

Dear Members, I am working on Elastic net and using R package for that. I have two matrix. My response is a matrix of size 50X50 and predictor is also in same size. I want to extract only cloumns from the matrix and do the elastic net analysis then store them as a matrix. library(elasticnet) library(lars) XB<-matrix(rnorm(2500,0,1), ncol=50,nrow=50) y1<-matrix(rnorm(2500,0,1),

Dear friends - We have 25 rats, 14 of these subjected to partial removal of kidney tissue, 11 to sham operation, and then followed for 6 weeks. So far we have data on 26 urine metabolites measured by NMR 7 times during the observation. I have smoothed the measurements by b.splines in fda including a roughness penalty, and inspecting the mean curves for nephrectomized and sham animals indicate

Dear All, I am using "Caret"package for SVM regression and elastic net regression . I can get the final fiited vs observed values. How can I get the coefficients? Any ideas? Thanks Alex [[alternative HTML version deleted]]

Hello, I'm trying to do some differential equation modeling in R using the package 'deSolve.' Briefly, I'm trying to use the law of mass action (the details of which aren't really important) to structure a vector of rate equation which will be passed into an ODE function and solved with associated functions from 'deSolve.' Roughly what this entails is scanning

Hi As I can't find an example of my data structure I'd like some advice on which is the most appropriate test for significant effects. If I should be using either lme or anova, is the relevant example below the best/correct way to do the test? The Data... 2 groups of patients (5 in GroupA, 7 in GroupB) 3 short acting drugs, (I'm not concerned with residual effects from the previous

Hi all, I have recently worked on fts plugin for ElasticSearch. https://github.com/filiphanes/fts-elastic It is forked from fts-elasticsearch as you can see in PR https://github.com/atkinsj/fts-elasticsearch/pull/21 with following changes (maybe some more) - no duplicate json keys in indexed documents, so compatible with ES 7.x - 1 elastic index for all users with routing by username -

Anyone have experience and willing to share for Beanstalk? e.g. How does Puppet fit in when we mainly use AWS Elastic Beanstalk? Seems most features are provided by Beanstalk. -- You received this message because you are subscribed to the Google Groups "Puppet Users" group. To post to this group, send email to puppet-users@googlegroups.com. To unsubscribe from this group, send email

Hi, List The elastic net package (by Hastie and Zou at Stanford) is used to do regularization and variable selection, it can also do regression. I am wondering if it can perform binary classification (discrete outcome). Anybody having similar experience? Many thanks, -Jack [[alternative HTML version deleted]]

Hi, I am having problems passing arguments to method="gbm" using the train() function. I would like to train gbm using the laplace distribution or the quantile distribution. here is the code I used and the error: gbm.test <- train(x.enet, y.matrix[,7], method="gbm", distribution=list(name="quantile",alpha=0.5), verbose=FALSE,

Hello, I'm writing to see if anyone here has had any success running Icecast2 (specifically I am using 2.4) on Amazon EC2 behind an Elastic Load Balancer? I have the ELB configured to do TCP loadbalancing rather than HTTP. I am able to connect and to stream music via the ELB, but when I disconnect, the listener count in Icecast does not decrease. On examining the state of the sockets table

Hello, I have this data: Time AMP 0 0.2000000 10 0.1958350 20 0.2914560 40 0.6763628 60 0.8494534 90 0.9874526 120 1.0477692 where AMP is the concentration of this metabolite with time. If you plot the data, you can see that it could be fitted using a logistic regression. For this purpose, I used this code: AMP.nls <- nls(AMP~SSlogis(Time,Asym, xmid, scal), data

Dear all, I am using modified LARS algorithm (ref: The Adaptive Lasso and Its Oracle Properties, Zou 2006) for adaptive lasso penalized linear regression. 1. w(j) <- |beta_ols(j)|^(-gamma) gamma>0 and j = 1,...,p 2. define x_new(j) <- x(j)*w(j) 3. apply LARS to solve modified lasso problem out.adalasso <- lars(X_new,y,type="lasso") or enet(X_new,

New versions of the caret (3.08) and caretLSF (1.12) packages have been released. caret (short for "Classification And REgression Training") aims to simplify the model building process. The package has functions for data splitting, pre-processing and model tuning, as well as other miscellaneous functions. In the new versions: - The elasticnet and the lasso (from the enet package)

New versions of the caret (3.08) and caretLSF (1.12) packages have been released. caret (short for "Classification And REgression Training") aims to simplify the model building process. The package has functions for data splitting, pre-processing and model tuning, as well as other miscellaneous functions. In the new versions: - The elasticnet and the lasso (from the enet package)

I have a backup server now restoring 6TB of data to a client machine. This has been going on for four days now, and no sign of getting close to completion. The connexion is Gb enet end-to-end, and is running at only 40Mb/s. It has far more capacity than that. The only limiting factor I can see is on the backup server one core of the CPU is running 100% rsync. Clearly rsync is not

Hi, I need to build ROC curve in R, can you please provide data steps / code or guide me through it. Thanks and Regards Rithesh M Mohan [[alternative HTML version deleted]]

So I won one of these on ebay, in the auction it says it has the RJ45 ports on it but it doesn't :( If I were to get an analog adapter would I be able to use the video portion of this or am I SOL? The auction requires me to pay for shipping back, so I end up losing money unless I sell it on my own. Or has anyone hacked these to work on enet?