All entries.
Showing Items 481-490 of 519 on page 49 of 52: First Previous 44 45 46 47 48 49 50 51 52 Next

Logo Variational Dirichlet process Gaussian mixtures 0.1

by kenkurihara - April 22, 2008, 01:41:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5819 views, 1194 downloads, 0 subscriptions

About: This is an implementation of variational Dirichlet process Gaussian mixtures. Thus, this works like the k-means, but it searched for the number of clusters as well. Couple algorithms are [...]

Changes:

Initial Announcement on mloss.org.


Logo r-cran-longRPart 1.0

by r-cran-robot - March 7, 2008, 00:00:00 CET [ Project Homepage BibTeX Download ] 888 views, 124 downloads, 0 subscriptions

About: Recursive partitioning of longitudinal data using mixed-effects models

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.201307


Logo BSVM 2.06

by biconnect - January 30, 2008, 10:27:13 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7025 views, 1307 downloads, 1 subscription

About: BSVM solves support vector machines (SVM) for the solution of large classification and regression problems. It includes three methods

Changes:

Initial Announcement on mloss.org.


Logo Python Robotics 5.0.0

by dsblank - January 22, 2008, 20:25:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5288 views, 1071 downloads, 1 subscription

About: The goal of the project is to provide a programming environment for easily exploring advanced topics in artificial intelligence and robotics without having to worry about the low-level details of [...]

Changes:

Initial Announcement on mloss.org.


About: The High-Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifier for high-dimensional data. This classifier is based on a mixture of Gaussian models adapted for [...]

Changes:

Initial Announcement on mloss.org.


Logo Learning the Kernel Matrix 1

by chap - January 14, 2008, 08:50:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5591 views, 1194 downloads, 1 subscription

About: Code for automatically selecting the kernel parameters of an SVM. It is based on a gradient descent minimization of either the radius/margin bound, the leave-one-out error, a validation error or the [...]

Changes:

Initial Announcement on mloss.org.


Logo TiMBL 6.1

by antalvdb - January 11, 2008, 09:20:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5094 views, 1158 downloads, 0 comments, 0 subscriptions

About: The TiMBL software package is a fast, decision-tree-based implementation of k-nearest neighbor classification. The package includes the IB1, IB2, TRIBL, TRIBL2, and IGTree algorithms, and offers [...]

Changes:

Initial Announcement on mloss.org.


Logo Vowpal Wabbit 2.3

by JohnLangford - December 21, 2007, 20:43:40 CET [ Project Homepage BibTeX Download ] 5721 views, 968 downloads, 0 subscriptions

Rating Whole StarWhole StarWhole StarWhole Star1/2 Star
(based on 2 votes)

About: This is a large scale online learning implementation with several useful features. See the webpage for more details.

Changes:

Initial Announcement on mloss.org.


Logo GPDT Gradient Projection Decomposition Technique 1.01

by sezaza - December 21, 2007, 20:10:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7936 views, 1393 downloads, 1 subscription

Rating Whole StarWhole StarWhole StarWhole StarEmpty Star
(based on 1 vote)

About: This is a C++ software designed to train large-scale SVMs for binary classification. The algorithm is also implemented in parallel (**PGPDT**) for distributed memory, strictly coupled multiprocessor [...]

Changes:

Initial Announcement on mloss.org.


About: TinyOS is a small operating for small (wireless) sensors. LEGO MINDSTORMS NXT is a platform for embedded systems experimentation: The combination of NXT and TinyOS is NXTMOTE.

Changes:

Initial Announcement on mloss.org.


Showing Items 481-490 of 519 on page 49 of 52: First Previous 44 45 46 47 48 49 50 51 52 Next