similar to: sparsenet: a new package for sparse model selection

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 .