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Logo JMLR LIBLINEAR 1.32

by biconnect - September 3, 2008, 17:35:24 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21004 views, 2435 downloads, 2 subscriptions

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About: LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, L1-loss linear SVM, and multi-class SVM

Changes:

Initial Announcement on mloss.org.


Logo Vowpal Wabbit 2.3

by JohnLangford - December 21, 2007, 20:43:40 CET [ Project Homepage BibTeX Download ] 7695 views, 1411 downloads, 1 subscription

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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 JMLR JKernelMachines 3.0

by dpicard - May 4, 2016, 17:53:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 33497 views, 7224 downloads, 4 subscriptions

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About: machine learning library in java for easy development of new kernels and kernel algorithms

Changes:

Version 3.0

/! Warning: this version is incompatible with previous code

  • change license to BSD 3-clauses
  • change package name to net.jkernelmachines
  • change to maven build system (available through central)
  • online training interfaces to allow continuous online learning
  • add a new budget oriented kernel classifier
  • new kernel and processing especially for strings

Logo JMLR DLLearner 1.0

by Jens - February 13, 2015, 11:39:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 23283 views, 5172 downloads, 6 subscriptions

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About: The DL-Learner framework contains several algorithms for supervised concept learning in Description Logics (DLs) and OWL.

Changes:

See http://dl-learner.org/development/changelog/.


Logo MDP Modular toolkit for Data Processing 3.3

by otizonaizit - October 4, 2012, 15:17:33 CET [ Project Homepage BibTeX Download ] 23930 views, 5883 downloads, 1 subscription

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About: MDP is a Python library of widely used data processing algorithms that can be combined according to a pipeline analogy to build more complex data processing software. The base of available algorithms includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.

Changes:

What's new in version 3.3?

  • support sklearn versions up to 0.12
  • cleanly support reload
  • fail gracefully if pp server does not start
  • several bug-fixes and improvements

Logo LIBSVM 2.9

by cjlin - February 27, 2010, 01:09:23 CET [ Project Homepage BibTeX Download ] 13638 views, 2855 downloads, 1 subscription

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About: LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC ), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class [...]

Changes:

Initial Announcement on mloss.org.


Logo Armadillo library 7.200

by cu24gjf - July 10, 2016, 15:44:07 CET [ Project Homepage BibTeX Download ] 96393 views, 19056 downloads, 5 subscriptions

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About: Armadillo is a high quality C++ linear algebra library, aiming towards a good balance between speed and ease of use. The function syntax is deliberately similar to MATLAB. Useful for algorithm development directly in C++, or quick conversion of research code into production environments (eg. software & hardware products).

Changes:
  • eigs_sym(), eigs_gen() and svds() now use a built-in reimplementation of ARPACK; contributed by Yixuan Qiu
  • faster handling of compound expressions by vectorise()
  • added .index_min() and .index_max()
  • added erf(), erfc(), lgamma()
  • added .head_slices() and .tail_slices() to subcube views
  • expanded ind2sub() to handle vectors of indices
  • expanded sub2ind() to handle matrix of subscripts
  • expanded expmat(), logmat() and sqrtmat() to optionally return a bool indicating success
  • spsolve() now requires SuperLU 5.2

Logo Lush 1.2.1

by ylecun - November 12, 2007, 06:35:08 CET [ Project Homepage BibTeX Download ] 6648 views, 2701 downloads, 0 subscriptions

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About: Lush is an object-oriented Lisp dialect with a super-simple way of integrating C/C++ code and libraries. It includes extensive libraries for numerical computing, machine learning, and computer [...]

Changes:

Initial Announcement on mloss.org.


Logo OpenOpt 0.54

by Dmitrey - June 15, 2014, 14:50:37 CET [ Project Homepage BibTeX Download ] 68081 views, 14051 downloads, 3 subscriptions

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About: Universal Python-written numerical optimization toolbox. Problems: NLP, LP, QP, NSP, MILP, LSP, LLSP, MMP, GLP, SLE, MOP etc; general logical constraints, categorical variables, automatic differentiation, stochastic programming, interval analysis, many other goodies

Changes:

http://openopt.org/Changelog


Logo Orange 2.6

by janez - February 14, 2013, 18:15:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 18261 views, 3540 downloads, 1 subscription

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About: Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...]

Changes:

The core of the system (except the GUI) no longer includes any GPL code and can be licensed under the terms of BSD upon request. The graphical part remains under GPL.

Changed the BibTeX reference to the paper recently published in JMLR MLOSS.


Showing Items 21-30 of 628 on page 3 of 63: Previous 1 2 3 4 5 6 7 8 Next Last