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Showing Items 151-160 of 595 on page 16 of 60: First Previous 11 12 13 14 15 16 17 18 19 20 21 Next Last

Logo BSVM 2.06

by biconnect - January 30, 2008, 10:27:13 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8284 views, 1590 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 Aleph 0.6

by jiria - January 12, 2009, 20:52:12 CET [ Project Homepage BibTeX Download ] 8275 views, 2343 downloads, 1 subscription

About: Aleph is both a multi-platform machine learning framework aimed at simplicity and performance, and a library of selected state-of-the-art algorithms.

Changes:

Initial Announcement on mloss.org.


Logo Somoclu 1.4.1

by peterwittek - January 28, 2015, 13:19:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8247 views, 1634 downloads, 2 subscriptions

About: Somoclu is a massively parallel implementation of self-organizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Apart from a command line interface, Python, R, and MATLAB are supported.

Changes:
  • Better support for ICC.
  • Faster code when compiling with GCC.
  • Building instructions and documentation improved.
  • Bug fixes: portability for R, using native R random number generator.

Logo VLFeat 0.9.16

by andreavedaldi - October 5, 2012, 18:44:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8098 views, 1514 downloads, 1 subscription

About: The VLFeat open source library implements popular computer vision algorithms including affine covariant feature detectors, HOG, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, and quick shift. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. The latest version of VLFeat is 0.9.16.

Changes:

VLFeat 0.9.16: Added VL_COVDET() (covariant feature detectors). This function implements the following detectors: DoG, Hessian, Harris Laplace, Hessian Laplace, Multiscale Hessian, Multiscale Harris. It also implements affine adaptation, estiamtion of feature orientation, computation of descriptors on the affine patches (including raw patches), and sourcing of custom feature frame. Addet the auxiliary function VL_PLOTSS(). This is the second point update supported by the PASCAL Harvest programme.

VLFeat 0.9.15: Added VL_HOG() (HOG features). Added VL_SVMPEGASOS() and a vastly improved SVM implementation. Added IHASHSUM (hashed counting). Improved INTHIST (integral histogram). Added VL_CUMMAX(). Improved the implementation of VL_ROC() and VL_PR(). Added VL_DET() (Detection Error Trade-off (DET) curves). Improved the verbosity control to AIB. Added support for Xcode 4.3, improved support for past and future Xcode versions. Completed the migration of the old test code in toolbox/test, moving the functionality to the new unit tests toolbox/xtest. Improved credits. This is the first point update supported by the PASCAL Harvest (several more to come shortly).


Logo Debellor 1.0

by mwojnars - July 30, 2009, 16:48:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8091 views, 2252 downloads, 1 subscription

About: Debellor is a scalable and extensible platform which provides common architecture for data mining and machine learning algorithms of various types.

Changes:
  • Naming of numerous classes/methods/fields changed to be more accurate and comprehensible
  • Weka and Rseslib libraries updated to the newest versions: Weka 3.6.1 & Rseslib 3.0.1. Debellor's wrappers adapted
  • New class: CrossValidation - evaluator of trainable cells through cross-validation
  • New class: RMSE - calculation of Root Mean Squared Error score
  • Data objects can be compared and used in collections
  • ArffReader can read from a user-provided java.io.InputStream
  • More convenient use of parameters (setting values)
  • More convenient use of data objects and data types (construction, type casting)
  • Other minor improvements to existing classes
  • Javadoc extended

Logo pGBRT, Parallel Gradient Boosted Regression Trees 0.9

by swtyree - September 16, 2011, 22:15:46 CET [ Project Homepage BibTeX Download ] 8023 views, 1299 downloads, 1 subscription

About: Learns gradient boosted regression tree ensembles in parallel on shared memory or cluster systems

Changes:

Initial Announcement on mloss.org.


Logo DeltaLDA 0.1.1

by davidandrzej - July 16, 2009, 21:52:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7992 views, 1417 downloads, 1 subscription

About: This software implements the DeltaLDA model, which is a modification of the Latent Dirichlet Allocation (LDA) model. DeltaLDA can use multiple topic mixing weight priors to jointly model multiple [...]

Changes:

-fixed some npy_intp[] memory leaks -fixed phi normalization bug


Logo r-cran-tree 1.0-29

by r-cran-robot - July 24, 2011, 00:00:00 CET [ Project Homepage BibTeX Download ] 7947 views, 1501 downloads, 1 subscription

About: Classification and regression trees

Changes:

Fetched by r-cran-robot on 2012-02-01 00:00:11.999664


Logo mcmkl 0.1

by ong - May 15, 2008, 15:30:44 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7843 views, 1581 downloads, 1 subscription

About: We provide some preliminary code for multiclass multiple kernel learning in Matlab using CPLEX as a base solver.

Changes:

Initial Announcement on mloss.org.


Logo BenchMarking Via Weka 0.0.4

by fracpete - December 4, 2008, 01:15:15 CET [ Project Homepage BibTeX Download ] 7830 views, 1391 downloads, 0 comments, 2 subscriptions

About: BenchMarking Via Weka is a client-server architecture that supports interoperability between different machine learning systems. Machine learning systems need to provide mechanisms for processing [...]

Changes:

Initial Announcement on mloss.org.


Showing Items 151-160 of 595 on page 16 of 60: First Previous 11 12 13 14 15 16 17 18 19 20 21 Next Last