Displaying 20 results from an estimated 600 matches similar to: "sparsenet: a new package for sparse model selection"

2013 Apr 02

0

softImpute_1.0 uploaded to CRAN

SoftImpute is a new package for matrix completion - i.e. for imputing missing values in matrices.
SoftImpute was written by myself and Rahul Mazumder.
softImpute uses uses squared-error loss with nuclear norm regularization - one can think of it as
the "lasso" for matrix approximation - to find a low-rank approximation to the observed entries in the matrix.
This low-rank approximation

2013 Apr 02

0

softImpute_1.0 uploaded to CRAN

SoftImpute is a new package for matrix completion - i.e. for imputing missing values in matrices.
SoftImpute was written by myself and Rahul Mazumder.
softImpute uses uses squared-error loss with nuclear norm regularization - one can think of it as
the "lasso" for matrix approximation - to find a low-rank approximation to the observed entries in the matrix.
This low-rank approximation

2017 Oct 21

1

What exactly is an dgCMatrix-class. There are so many attributes.

> On Oct 21, 2017, at 7:50 AM, Martin Maechler <maechler at stat.math.ethz.ch> wrote:
>
>>>>>> C W <tmrsg11 at gmail.com>
>>>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes:
>
>> Thank you for your responses. I guess I don't feel
>> alone. I don't find the documentation go into any detail.
>
>> I also find

2007 Sep 07

1

Finding convex hull?

Dear UseRs,
I would like to know which function is the most efficient in finding
convex hull of points in 3(or 2)-dimensional case?
Functions for finding convex hull is the following:
convex.hull (tripack), chull (grDevices), in.chull (sgeostat),
convhulln (geometry), convexhull.xy (spatstat), calcConvexHull
(PBSmapping).
I also would like to know if there is a function that can be used

2013 Mar 02

0

glmnet 1.9-3 uploaded to CRAN (with intercept option)

This update adds an intercept option (by popular request) - now one can fit a model without an intercept
Glmnet is a package that fits the regularization path for a number of generalized linear models, with with "elastic net"
regularization (tunable mixture of L1 and L2 penalties). Glmnet uses pathwise coordinate descent, and is very fast.
The current list of models covered are:

2013 Mar 02

0

glmnet 1.9-3 uploaded to CRAN (with intercept option)

This update adds an intercept option (by popular request) - now one can fit a model without an intercept
Glmnet is a package that fits the regularization path for a number of generalized linear models, with with "elastic net"
regularization (tunable mixture of L1 and L2 penalties). Glmnet uses pathwise coordinate descent, and is very fast.
The current list of models covered are:

2007 Mar 26

1

sampling from the uniform distribution over a convex hull

Ranjan Maitra writes:
> Does anyone have a suggestion (or better still) code for sampling
> from the uniform distribution over the convex hull of a set of
> points?
This is implemented in library 'spatstat'.
If x and y are vectors of coordinates of your initial set of points,
library(spatstat)
W <- convexhull.xy(x, y)
P <- runifpoint(42, W)
will compute

2014 Oct 12

1

Is xyz point inside 3d convex hull?

Hi everyone,
I wonder if there is a code in r that can generate a 3d convex hull from a data-frame containing 3 columns and then use another database with the same three columns and for each row determine if the xyz point is inside or not the convex hull generated with the first database?
The package geometry allows to calculate a hull and it's volume. I was planning to calculate the volume

2017 Oct 21

0

What exactly is an dgCMatrix-class. There are so many attributes.

>>>>> C W <tmrsg11 at gmail.com>
>>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes:
> Thank you for your responses. I guess I don't feel
> alone. I don't find the documentation go into any detail.
> I also find it surprising that,
>> object.size(train$data)
> 1730904 bytes
>>

2017 Nov 21

0

[R-pkgs] CVXR: Convex Programming in R

Dear R Users,
We are pleased to announce the first release of CVXR which implements
Disciplined Convex Programming (DCP) in R on CRAN. Like CVXPY in Python,
CVXR provides a domain specific language for formulating
convexoptimization problems in a natural way following mathematical
convention and DCP rules. The system analyzes the problem, verifies its
convexity, converts it into a canonical

2001 Dec 10

1

high dimensional convex hull

Does anyone know of a R package that will determine the convex hull of a
high-dimensional dataset (say 4-10 dimensions). I know chull works for
2D data.
I'm neophyte to R and convex hulls so please keep it simple.
Many thanks
Ben
--
Ben Stapley.
Biomolecular Sciences, UMIST, PO Box 88, Manchester M60 1QD.
Tel 0161 200 5818
Fax 0161 236 0409

2010 Dec 20

0

survexp - unable to reproduce example

Dear All,
when I try to reproduce an example of survexp, taken from the help
page of survdiff, I receive the error message
"Error in floor(temp) : Non-numeric argument to mathematical function"
.
It seems to come from match.ratetable. I think, it has to do with
character variables in a ratetable.
I would be interested to know, if it works for others. With an older
version of

2013 Mar 05

2

Questions on implementing logistic regression

Hi there,
I am trying to write a tool which involves implementing logistic
regression. With the batch gradient descent method, the convergence is
guaranteed as it is a convex problem. However, I find that with the
stochastic gradient decent method, it typically converges to some random
points (i.e., not very close to the minimum point resulted from the batch
method). I have tried different ways

2006 May 12

1

[ESRI-L] outline polygons of point clumps

Sorry, I did not make my question clear. Since I have a point theme
with many points, some of them may clump together. the problems here
are:
1. how to find clumps in a point theme?
2. the convex-hull extension I found only deal with all the points in
a theme at each time? how to make each convex hull around each point
clump automatically?
Thanks.
Xiaohua
On 5/12/06, Bob Booth

2004 Jun 01

0

qhull in R?

Hi,
does anyone know if there is an implementation
of qhull (http://www.qhull.org/) in R? anyone is
planning on it?
"Qhull computes convex hulls, Delaunay triangulations, halfspace
intersections about a point, Voronoi diagrams, furthest-site Delaunay
triangulations, and furthest-site Voronoi diagrams. It runs in 2-d, 3-d,
4-d, and higher dimensions. It implements the

2010 Apr 04

0

Major glmnet upgrade on CRAN

glmnet_1.2 has been uploaded to CRAN.
This is a major upgrade, with the following additional features:
* poisson family, with dense or sparse x
* Cox proportional hazards family, for dense x
* wide range of cross-validation features. All models have several criteria for cross-validation.
These include deviance, mean absolute error, misclassification error and "auc" for logistic or

2010 Apr 04

0

Major glmnet upgrade on CRAN

glmnet_1.2 has been uploaded to CRAN.
This is a major upgrade, with the following additional features:
* poisson family, with dense or sparse x
* Cox proportional hazards family, for dense x
* wide range of cross-validation features. All models have several criteria for cross-validation.
These include deviance, mean absolute error, misclassification error and "auc" for logistic or

2010 Nov 04

0

glmnet_1.5 uploaded to CRAN

This is a new version of glmnet, that incorporates some bug fixes and
speedups.
* a new convergence criterion which which offers 10x or more speedups for
saturated fits (mainly effects logistic, Poisson and Cox)
* one can now predict directly from a cv.object - see the help files for cv.glmnet
and predict.cv.glmnet
* other new methods are deviance() for "glmnet" and coef() for

2003 Jul 18

1

Grandstream BudgeTone 102 initial experiences

Just to toss in my very limited experiences with the Grandstream phone--
I haven't tested it enough to really know nor is my Asterisk
config set up enough to fully try all the features.
Mostly, it just works. It was very easy to configure and
get running. I've been toting it around to clients as a
show and tell exhibit and it has helped get people excited
about the possibilities.
Voice

2017 Oct 20

0

What exactly is an dgCMatrix-class. There are so many attributes.

Subsetting using [] vs. head(), gives different results.
R code:
> head(train$data, 5)
[1] 0 0 1 0 0
> train$data[1:5, 1:5]
5 x 5 sparse Matrix of class "dgCMatrix"
cap-shape=bell cap-shape=conical cap-shape=convex
[1,] . . 1
[2,] . . 1
[3,] 1 .