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Logo BSVM 2.06

by biconnect - January 30, 2008, 10:27:13 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7801 views, 1477 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 ] 2026 views, 465 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 ] 5244 views, 1245 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 ] 2850 views, 719 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.


Logo Caffe 0.9999

by sergeyk - August 9, 2014, 01:57:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5607 views, 949 downloads, 2 subscriptions

About: Caffe aims to provide computer vision scientists with a clean, modifiable implementation of state-of-the-art deep learning algorithms. We believe that Caffe is the fastest available GPU CNN implementation. Caffe also provides seamless switching between CPU and GPU, which allows one to train models with fast GPUs and then deploy them on non-GPU clusters. Even in CPU mode, computing predictions on an image takes only 20 ms (in batch mode).

Changes:

LOTS of stuff: https://github.com/BVLC/caffe/releases/tag/v0.9999


Logo Calculate Normalized Information Measures 1.0.0

by openpr_nlpr - December 2, 2011, 04:35:32 CET [ Project Homepage BibTeX Download ] 1272 views, 401 downloads, 1 subscription

About: The toolbox is to calculate normalized information measures from a given m by (m+1) confusion matrix for objective evaluations of an abstaining classifier. It includes total 24 normalized information measures based on three groups of definitions, that is, mutual information, information divergence, and cross entropy.

Changes:

Initial Announcement on mloss.org.


Logo JMLR CAM Java 3.1

by wangny - October 14, 2013, 22:46:03 CET [ Project Homepage BibTeX Download ] 6991 views, 3060 downloads, 1 subscription

About: The CAM R-Java software provides a noval way to solve blind source separation problem.

Changes:

In this version, we fix the problem of not working under newest R version R-3.0.


Logo JMLR CARP 3.3

by volmeln - November 7, 2013, 15:48:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 16063 views, 5162 downloads, 1 subscription

About: CARP: The Clustering Algorithms’ Referee Package

Changes:

Generalized overlap error and some bugs have been fixed


Logo cbMDS Correlation Based Multi Dimensional Scaling 1.2

by emstrick - July 27, 2013, 14:35:36 CET [ BibTeX BibTeX for corresponding Paper Download ] 3995 views, 974 downloads, 1 subscription

About: The aim is to embed a given data relationship matrix into a low-dimensional Euclidean space such that the point distances / distance ranks correlate best with the original input relationships. Input relationships may be given as (sparse) (asymmetric) distance, dissimilarity, or (negative!) score matrices. Input-output relations are modeled as low-conditioned. (Weighted) Pearson and soft Spearman rank correlation, and unweighted soft Kendall correlation are supported correlation measures for input/output object neighborhood relationships.

Changes:
  • Initial release (Ver 1.0): Weighted Pearson and correlation and soft Spearman rank correlation, Tue Dec 4 16:14:51 CET 2012

  • Ver 1.1 Added soft Kendall correlation, Fri Mar 8 08:41:09 CET 2013

  • Ver 1.2 Added reconstruction of sparse relationship matrices, Fri Jul 26 16:58:37 CEST 2013


Logo CFSPCommunityDetection 1.0

by tbuehler - October 13, 2014, 05:36:24 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 865 views, 210 downloads, 1 subscription

About: A community detection method based on constrained fractional set programming (CFSP).

Changes:

Initial Announcement on mloss.org.


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