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Logo BioSig for Octave and Matlab 2.31

by schloegl - July 28, 2009, 13:41:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10672 views, 1745 downloads, 0 subscriptions

About: BioSig is a software library for biomedical signal processings. Besides several other modules, one modul (t400) provides a common interface (train_sc.m and test_sc.m) to various classification [...]

Changes:

Update of project information: machine learning and classification tools are moved to the NaN-toolbox.


Logo BMRM 2.1

by chteo - May 8, 2009, 08:08:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5674 views, 1103 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 bob 1.2.2

by anjos - October 28, 2013, 14:37:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5285 views, 1106 downloads, 1 subscription

About: Bob is a free signal-processing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland.

Changes:

Bob 1.2.0 comes about 1 year after we released Bob 1.0.0. This new release comes with a big set of new features and lots of changes under the hood to make your experiments run even smoother. Some statistics:

Diff URL: https://github.com/idiap/bob/compare/v1.1.4...HEAD Commits: 629 Files changed: 954 Contributors: 7

Here is a quick list of things you should pay attention for while integrating your satellite packages against Bob 1.2.x:

  • The LBP module had its API changed look at the online docs for more details
  • LLRTrainer has been renamed to CGLogRegTrainer
  • The order in which you pass data to CGLogRegTrainer has been inverted (negatives now go first)
  • For C++ bindings, includes are in bob/python instead of bob/core/python
  • All specialized Bob exceptions are gone, if you were catching them, most have been cast into std::runtime_error's

For a detailed list of changes and additions, please look at our Changelog page for this release and minor updates:

https://github.com/idiap/bob/wiki/Changelog-from-1.1.4-to-1.2 https://github.com/idiap/bob/wiki/Changelog-from-1.2.0-to-1.2.1 https://github.com/idiap/bob/wiki/Changelog-from-1.2.1-to-1.2.2


Logo Boosted Decision Trees and Lists 1.0.4

by melamed - July 25, 2014, 23:08:32 CET [ BibTeX Download ] 2854 views, 864 downloads, 3 subscriptions

About: Boosting algorithms for classification and regression, with many variations. Features include: Scalable and robust; Easily customizable loss functions; One-shot training for an entire regularization path; Continuous checkpointing; much more

Changes:
  • added ElasticNets as a regularization option
  • fixed some segfaults, memory leaks, and out-of-range errors, which were creeping in in some corner cases
  • added a couple of I/O optimizations

Logo boostree 0.1

by xavierc - December 1, 2007, 03:16:14 CET [ BibTeX Download ] 3909 views, 1355 downloads, 0 comments, 0 subscriptions

About: This package provides an implementation Schapire and Singer's AdaBoost.MH for multi-label classification. As a main feature, the package provides decision-tree weak learning, a generalization of [...]

Changes:

Initial Announcement on mloss.org.


Logo BRML toolbox 070711

by DavidBarber - July 17, 2011, 19:30:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 58213 views, 3630 downloads, 1 subscription

About: Bayesian Reasoning and Machine Learning toolbox

Changes:

Fixed some small bugs and updated some demos.


Logo BSVM 2.06

by biconnect - January 30, 2008, 10:27:13 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7429 views, 1400 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 JMLR BudgetedSVM v1.1

by nemanja - February 12, 2014, 20:53:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1423 views, 284 downloads, 1 subscription

About: BudgetedSVM is an open-source C++ toolbox for scalable non-linear classification. The toolbox can be seen as a missing link between LibLinear and LibSVM, combining the efficiency of linear with the accuracy of kernel SVM. We provide an Application Programming Interface for efficient training and testing of non-linear classifiers, supported by data structures designed for handling data which cannot fit in memory. We also provide command-line and Matlab interfaces, providing users with an efficient, easy-to-use tool for large-scale non-linear classification.

Changes:

Changed license from LGPL v3 to Modified BSD.


Logo C MixSim 0.5

by volmeln - June 10, 2009, 19:37:42 CET [ Project Homepage BibTeX Download ] 4850 views, 1151 downloads, 1 subscription

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About: C-MixSim is an open source package written in C for simulating finite mixture models with Gaussian components. With a vast number of clustering algorithms, evaluating performance is important. C-MixSim provides an easy and convenient way of generating datasets from Gaussian mixture models with different levels of clustering complexity. C-MixSim is released under the GNU GPL license.

Changes:

Initial Announcement on mloss.org.


Logo C5.0 2.07

by zenog - September 2, 2011, 14:49:04 CET [ Project Homepage BibTeX Download ] 2554 views, 642 downloads, 1 subscription

About: C5.0 is the successor of the C4.5 decision tree algorithm/tool. In particular, it is faster and more memory-efficient.

Changes:

Initial Announcement on mloss.org.


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