6 projects found that use the mpl 1.1 license.


Logo Generalised Stirling Numbers libstb 1.0 1.4

by wbuntine - September 28, 2012, 13:49:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4512 views, 840 downloads, 1 subscription

About: THIS VERSION DISCONTINUED, see "http://mloss.org/software/view/424/". This library provides ways of computing generalised 2nd-order Stirling numbers for Pitman-Yor and Dirichlet processes. Included is a tester and parameter optimiser. This accompanies Buntine and Hutter's article: http://arxiv.org/abs/1007.0296

Changes:

See the alternative MLOSS entry "libstb". Updated to 1.4!


Logo Elefant 0.4

by kishorg - October 17, 2009, 08:48:19 CET [ Project Homepage BibTeX Download ] 15904 views, 7220 downloads, 2 subscriptions

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About: Elefant is an open source software platform for the Machine Learning community licensed under the Mozilla Public License (MPL) and developed using Python, C, and C++. We aim to make it the platform [...]

Changes:

This release contains the Stream module as a first step in the direction of providing C++ library support. Stream aims to be a software framework for the implementation of large scale online learning algorithms. Large scale, in this context, should be understood as something that does not fit in the memory of a standard desktop computer.

Added Bundle Methods for Regularized Risk Minimization (BMRM) allowing to choose from a list of loss functions and solvers (linear and quadratic).

Added the following loss classes: BinaryClassificationLoss, HingeLoss, SquaredHingeLoss, ExponentialLoss, LogisticLoss, NoveltyLoss, LeastMeanSquareLoss, LeastAbsoluteDeviationLoss, QuantileRegressionLoss, EpsilonInsensitiveLoss, HuberRobustLoss, PoissonRegressionLoss, MultiClassLoss, WinnerTakesAllMultiClassLoss, ScaledSoftMarginMultiClassLoss, SoftmaxMultiClassLoss, MultivariateRegressionLoss

Graphical User Interface provides now extensive documentation for each component explaining state variables and port descriptions.

Changed saving and loading of experiments to XML (thereby avoiding storage of large input data structures).

Unified automatic input checking via new static typing extending Python properties.

Full support for recursive composition of larger components containing arbitrary statically typed state variables.


Logo BMRM 2.1

by chteo - May 8, 2009, 08:08:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5446 views, 1049 downloads, 1 subscription

About: BMRM is an open source, modular and scalable convex solver for many machine learning problems cast in the form of regularized risk minimization problem.

Changes:

Initial Announcement on mloss.org.


Logo CoFiRank 0.1

by alexis - March 30, 2009, 17:17:34 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4728 views, 949 downloads, 2 subscriptions

About: CoFiRank is a Collaborative Filtering system based on matrix factorization. CoFiRank is based on the idea that it is better to predict the relative order of preferences (ranking) instead of the absolute rating.

Changes:

Initial Announcement on mloss.org.


Logo LibPG 126

by daa - December 3, 2007, 19:59:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5328 views, 1072 downloads, 0 subscriptions

About: The PG library is a high-performance reinforcement learning library. The name PG refers to policy-gradient methods, but this name is largely historical. The library also impliments value-based RL [...]

Changes:

Initial Announcement on mloss.org.


Logo gboost 0.1.1

by nowozin - November 4, 2007, 07:52:21 CET [ Project Homepage BibTeX Download ] 5340 views, 1083 downloads, 0 subscriptions

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About: The gboost toolbox is a framework for classification of connected, undirected, labeled graphs.

Changes:

Initial Announcement on mloss.org.


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