Displaying 20 results from an estimated 6000 matches similar to: "LASSO coefficients for a specific s"
2007 Jun 12
1
LASSO coefficients for a specific s
Hello,
I have a question about the lars package. I am using this package to get the coefficients at a specific LASSO parameter s.
data(diabetes)
attach(diabetes)
object <- lars(x,y,type="lasso")
cvres<-cv.lars(x,y,K=10,fraction = seq(from = 0, to = 1, length = 100))
fits <- predict.lars(object, type="coefficients", s=0.1, mode="fraction")
Can I assign
2007 Mar 15
1
Model selection in LASSO (cross-validation)
Hi, I know how to use LASSO for model selection based on the Cp criterion.
I heard that we can also use cross validation as a criterion too. I used
cv.lars to give me the lowest predicted error & fraction. But I'm short of
a step to arrive at the number of variables to be included in the final
model. How do we do that? Is it the predict.lars function? i tried >
2011 May 24
1
seeking help on using LARS package
Hi,
I am writing to seek some guidance regarding using Lasso regression with the
R package LARS. I have introductory statistics background but I am trying to
learn more. Right now I am trying to duplicate the results in a paper for
shRNA prediction "An accurate and interpretable model for siRNA efficacy
prediction, Jean-Philippe Vert et. al, Bioinformatics" for a Bioinformatics
project
2010 Dec 06
2
How to get lasso fit coefficient(given penalty tuning parameter \lambda) using lars package
Hi, all,
I am using the lars package for lasso estimate. So I get a lasso
fit first:
lassofit = lars(x,y,type ="lasso",normalize=T, intercept=T)
Then I want to get coefficient with respect to a certain value of \lambda
(the tuning parameter), I know lars has three mode options c("step",
"fraction", "norm"), but can I use the \lambda value instead
2009 Dec 16
0
lasso regression coefficients
Dear list,
I have been trying to apply a simple lasso regression on a 10-element
vector, just to see how this method works so as to later implement it on
larger datasets. I thus create an input vector x:
* x=rnorm(10)*
I add some noise
* noise=runif(n=10, min=-0.1, max=0.1)*
and I create a simple linear model which calculates my output vector y
* y=2*x+1+noise*
I then do
2009 Aug 21
1
LASSO: glmpath and cv.glmpath
Hi,
perhaps you can help me to find out, how to find the best Lambda in a
LASSO-model.
I have a feature selection problem with 150 proteins potentially
predicting Cancer or Noncancer. With a lasso model
fit.glm <- glmpath(x=as.matrix(X), y=target, family="binomial")
(target is 0, 1 <- Cancer non cancer, X the proteins, numerical in
expression), I get following path (PICTURE
2010 Apr 06
1
Caret package and lasso
Dear all,
I have used following code but everytime I encounter a problem of not having
coefficients for all the variables in the predictor set.
# code
rm(list=ls())
library(caret)
# generating response and design matrix
X<-matrix(rnorm(50*100),nrow=50)
y<-rnorm(50*1)
# Applying caret package
con<-trainControl(method="cv",number=10)
data<-NULL
data<- train(X,y,
2017 Oct 31
0
lasso and ridge regression
Dear All
The problem is about regularization methods in multiple regression when the
independent variables are collinear. A modified regularization method with
two tuning parameters l1 and l2 and their product l1*l2 (Lambda 1 and
Lambda 2) such that l1 takes care of ridge property and l2 takes care of
LASSO property is proposed
The proposed method is given
2011 May 28
1
Questions regrading the lasso and glmnet
Hi all. Sorry for the long email. I have been trying to find someone local to work on this with me, without much luck. I went in to our local stats consulting service here, and the guy there told me that I already know more about model selection than he does. :-< He pointed me towards another professor that can perhaps help, but that prof is busy until mid-June, so I want to get as much
2012 Jun 16
0
Selecting correlated predictors with LASSO
I'm using the package 'lars' in R with the following code:
> library(lars)
> set.seed(3)
> n <- 1000
> x1 <- rnorm(n)
> x2 <- x1+rnorm(n)*0.5
> x3 <- rnorm(n)
> x4 <- rnorm(n)
> x5 <- rexp(n)
> y <- 5*x1 + 4*x2 + 2*x3 + 7*x4 + rnorm(n)
> x <- cbind(x1,x2,x3,x4,x5)
> cor(cbind(y,x))
y x1 x2
2011 Jun 06
1
Lasso for k-subset regression
Dear R-users
I'm trying to use lasso in lars package for subset regression, I have a
large matrix of size 1000x100 and my aim is to select a subset k of the 100
variables.
Is there any way in lars to fix the number k (i.e. to select the best 10
variables)
library(lars)
aa=lars(X,Y,type="lasso",max.steps=200)
plot(aa,plottype="Cp")
aa$RSS
which.min(aa$RSS)
2011 Jul 12
7
FW: lasso regression
Hi,
I am trying to do a lasso regression using the lars package with the following data (see attached):
FastestTime
WinPercentage
PlacePercentage
ShowPercentage
BreakAverage
FinishAverage
Time7Average
Time3Average
Finish
116.90
0.14
0.14
0.29
4.43
3.29
117.56
117.77
5.00
116.23
0.29
0.43
0.14
6.14
2.14
116.84
116.80
2.00
116.41
0.00
0.14
0.29
5.71
3.71
117.24
2007 Aug 02
2
lasso/lars error
I'm having the exact problem outlined in a previous post from 2005 -
unfortunately the post was never answered:
http://tolstoy.newcastle.edu.au/R/help/05/10/15055.html
When running:
lm2=lars(x2,y,type="lasso",use.Gram=F)
I get an error:
Error in if (zmin < gamhat) { : missing value where TRUE/FALSE needed
...when running lasso via lars() on a 67x3795 set of predictors. I
2012 Jun 05
1
Piecewise Lasso Regression
Hi All,
I am trying to fit a piecewise lasso regression, but package Segmented does not work with Lars objects.
Does any know of any package or implementation of piecewise lasso regression?
Thanks,
Lucas
2006 Mar 06
0
Problems with R CMD Rdconv and R CMD Sd2Rd (PR#8661)
I'm using R 2.2.0 on Windows.
Doing some conversions of help files. Internal comments indicate
that the Sd2Rd conversion is "Converted by Sd2Rd version 1.21."
I'm converting
.d -> .Rd
.sgml -> .Rd
using Sd2Rd, then checking by using Rdconv to
convert .Rd back to .d or .sgml.
Here are errors in some of the conversions.
The most significant errors are in .Rd to .sgml.
2011 May 02
2
Lasso with Categorical Variables
Hi! This is my first time posting. I've read the general rules and
guidelines, but please bear with me if I make some fatal error in
posting. Anyway, I have a continuous response and 29 predictors made
up of continuous variables and nominal and ordinal categorical
variables. I'd like to do lasso on these, but I get an error. The way
I am using "lars" doesn't allow for the
2006 Aug 14
1
lasso for variable selection
For "importance" it's probably best to stick with absolute values of
coefficients, instead of value of the penalty parameter for which the
coefficients changed to non-zero.
Friedman skipped a lot of details on his rule ensemble in that talk, due to
time constraint. In his implementation he was using his own algorithm,
PathSeeker, for which paper and software are available on his
2013 May 04
2
Lasso Regression error
Hi all,
I have a data set containing variables LOSS, GDP, HPI and UE.
(I have attached it in case it is required).
Having renamed the variables as l,g,h and u, I wish to run a Lasso
Regression with l as the dependent variable and all the other 3 as the
independent variables.
data=read.table("data.txt", header=T)
l=data$LOSS
h=data$HPI
u=data$UE
g=data$GDP
matrix=data.frame(l,g,h,u)
2011 May 01
1
Different results of coefficients by packages penalized and glmnet
Dear R users:
Recently, I learn to use penalized logistic regression. Two packages
(penalized and glmnet) have the function of lasso.
So I write these code. However, I got different results of coef. Can someone
kindly explain.
# lasso using penalized
library(penalized)
pena.fit2<-penalized(HRLNM,penalized=~CN+NoSus,lambda1=1,model="logistic",standardize=TRUE)
pena.fit2
2003 Jun 13
1
lars - lasso problem
hello
I tried to use lars() but neither with my own data nor with the sample data it
works. I get in both cases the following error prompt:
> data(diabetes)
> par(mfrow=c(2,2))
> attach(diabetes)
> x<-lars(x,y)
Error in one %*% x : requires numeric matrix/vector arguments
> x<-lars(x,y, type="lasso")
Error in one %*% x : requires numeric matrix/vector arguments