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Logo MPI IKL 1.0

by pgehler - January 16, 2009, 16:39:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7221 views, 1368 downloads, 1 subscription

About: This package contains an implementation of the Infinite Kernel Learning (IKL) algorithm and the SimpleMKL algorithm. This is realized by building on Coin-Ipopt-3.3.5 and Libsvm.

Changes:

Initial Announcement on mloss.org.


Logo Spike train feature extraction by Bayesian binning 0.1

by dendres - September 24, 2008, 16:19:14 CET [ BibTeX BibTeX for corresponding Paper Download ] 5684 views, 1367 downloads, 0 comments, 1 subscription

About: *binsdfc* is a command line implementation of the algorithm described in [Endres,Oram,Schindelin,Foldiak:*Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms*, [...]

Changes:

Changed build system from automake to cmake. Moved download page to www.compsens.uni-tuebingen.de


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 ] 8097 views, 1366 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 Graph Learning Package 0.1

by hiroto - May 4, 2009, 17:07:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7219 views, 1364 downloads, 0 subscriptions

About: This software is aimed at performing supervised/unsupervised learning on graph data, where each graph is represented as binary indicators of subgraph features.

Changes:

Initial Announcement on mloss.org.


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 ] 6473 views, 1347 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 Learning the Kernel Matrix 1

by chap - January 14, 2008, 08:50:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6167 views, 1346 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 Local Alignment Kernels 0.3.2

by hiroto - December 1, 2007, 00:10:23 CET [ Project Homepage BibTeX Download ] 5676 views, 1343 downloads, 0 subscriptions

About: Local alignment kernels measure the similarity between two sequences by summing up scores obtained from local alignments with gaps of the sequences.

Changes:

Initial Announcement on mloss.org.


Logo scikits.learn 0.6

by fabianp - December 22, 2010, 11:58:30 CET [ Project Homepage BibTeX Download ] 6965 views, 1342 downloads, 1 subscription

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About: Obsolete. Use https://mloss.org/software/view/240/ instead.

Changes:

0.6 release


Logo SCD 2.1

by ambujtewari - December 3, 2009, 22:21:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6953 views, 1338 downloads, 1 subscription

About: A (randomized) coordinate descent procedure to minimize L1 regularized loss for classification and regression purposes.

Changes:

Fixed some I/O bugs. Lines that ended with whitespace were not read correctly in the previous version.


Logo Alchemy 0.33

by marcs - December 16, 2008, 17:53:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5487 views, 1338 downloads, 1 subscription

About: Alchemy is a software package providing a series of algorithms for statistical relational learning and probabilistic logic inference, based on the Markov logic representation. Alchemy allows you to [...]

Changes:

Initial Announcement on mloss.org.


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