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Showing Items 131-140 of 579 on page 14 of 58: First Previous 9 10 11 12 13 14 15 16 17 18 19 Next Last

Logo Easysvm 0.3

by gxr - June 25, 2009, 18:33:04 CET [ Project Homepage BibTeX Download ] 8586 views, 1662 downloads, 1 subscription

About: The Easysvm package provides a set of tools based on the Shogun toolbox allowing to train and test SVMs in a simple way.

Changes:

Fixes for shogun 0.7.3.


About: OpenGM is a free C++ template library, a command line tool and a set of MATLAB functions for optimization in higher order graphical models. Graphical models of any order and structure can be built either in C++ or in MATLAB, using simple and intuitive commands. These models can be stored in HDF5 files and subjected to state-of-the-art optimization algorithms via the OpenGM command line optimizer. All library functions can also be called directly from C++ code. OpenGM realizes the Inference Algorithm Interface (IAI), a concept that makes it easy for programmers to use their own algorithms and factor classes with OpenGM.

Changes:

Initial Announcement on mloss.org.


Logo Graph kernel based on iterative graph similarity and optimal assignments 2008-01-15

by mrupp - September 22, 2008, 13:42:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8196 views, 1389 downloads, 2 subscriptions

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About: Java package implementing a kernel for (molecular) graphs based on iterative graph similarity and optimal assignments.

Changes:

Initial Announcement on mloss.org.


Logo asp 0.3

by sonne - May 7, 2010, 10:25:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8187 views, 1635 downloads, 1 subscription

About: Accurate splice site predictor for a variety of genomes.

Changes:

Asp now supports three formats:

-g fname for gff format

-s fname for spf format

-b dir for a binary format compatible with mGene.

And a new switch

-t which switches on a sigmoid-based transformation of the svm scores to get scores between 0 and 1.


Logo OptWok 0.3.1

by ong - May 2, 2013, 10:46:11 CET [ Project Homepage BibTeX Download ] 8104 views, 1557 downloads, 1 subscription

About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier.

Changes:
  • minor bugfix

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 Adaptive Resonance Theory for Unsupervised Learning 1.0

by ibaze - November 13, 2008, 16:40:28 CET [ Project Homepage BibTeX Download ] 7982 views, 1869 downloads, 1 subscription

About: This software package includes the ART algorithms for unsupervised learning only. It is a family of four programs based on different ART algorithms (ART 1, ART 2A, ART 2A-C and ART Distance). All of [...]

Changes:

Initial Announcement on mloss.org.


Logo pymaBandits 1.0

by garivier - July 6, 2012, 18:32:41 CET [ BibTeX Download ] 7979 views, 1384 downloads, 1 subscription

About: This package contains a python and a matlab implementation of the most widely used algorithms for multi-armed bandit problems. The purpose of this package is to provide simple environments for comparison and numerical evaluation of policies.

Changes:

Initial Announcement on mloss.org.


About: Matlab code for performing variational inference in the Indian Buffet Process with a linear-Gaussian likelihood model.

Changes:

Initial Announcement on mloss.org.


Logo 1SpectralClustering 1.1

by tbuehler - June 27, 2011, 10:45:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7840 views, 1494 downloads, 1 subscription

About: A fast and scalable graph-based clustering algorithm based on the eigenvectors of the nonlinear 1-Laplacian.

Changes:
  • fixed bug occuring when input graph is disconnected
  • reduced memory usage when input graph has large number of disconnected components
  • more user-friendly usage of main method OneSpectralClustering
  • faster computation of eigenvector initialization + now thresholded according to multicut-criterion
  • several internal optimizations

Showing Items 131-140 of 579 on page 14 of 58: First Previous 9 10 11 12 13 14 15 16 17 18 19 Next Last