Projects that are tagged with machine learning.
Showing Items 21-40 of 69 on page 2 of 4: Previous 1 2 3 4 Next

Logo JMLR Darwin 1.9

by sgould - September 8, 2015, 06:50:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 69161 views, 14095 downloads, 4 subscriptions

About: A platform-independent C++ framework for machine learning, graphical models, and computer vision research and development.

Changes:

Version 1.9:

  • Replaced drwnInPaint class with drwnImageInPainter class and added inPaint application
  • Added function to read CIFAR-10 and CIFAR-100 style datasets (see http://www.cs.utoronto.ca/~kriz/cifar.html)
  • Added drwnMaskedPatchMatch, drwnBasicPatchMatch, drwnSelfPatchMatch and basicPatchMatch application
  • drwnPatchMatchGraph now allows multiple matches to the same image
  • Upgraded wxWidgets to 3.0.2 (problems on Mac OS X)
  • Switched Mac OS X compilation to libc++ instead of libstdc++
  • Added Python scripts for running experiments and regression tests
  • Refactored drwnGrabCutInstance class to support both GMM and colour histogram model
  • Added cacheSortIndex to drwnDecisionTree for trading-off speed versus memory usage
  • Added mexLoadPatchMatchGraph for loading drwnPatchMatchGraph objects into Matlab
  • Improved documentation, other bug fixes and performance improvements

Logo YCML 0.2.2

by yconst - August 24, 2015, 20:28:45 CET [ Project Homepage BibTeX Download ] 2592 views, 580 downloads, 3 subscriptions

About: A Machine Learning framework for Objective-C and Swift (OS X / iOS)

Changes:

Initial Announcement on mloss.org.


About: R package implementing statistical test and post hoc tests to compare multiple algorithms in multiple problems.

Changes:

Initial Announcement on mloss.org.


Logo Nilearn 0.1.2

by goulagman - April 29, 2015, 16:16:25 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4376 views, 997 downloads, 3 subscriptions

About: Nilearn is a Python module for fast and easy statistical learning on NeuroImaging data. It leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis.

Changes:

Initial Announcement on mloss.org.


Logo Choquistic Utilitaristic Regression 1.00

by AliFall - April 17, 2015, 11:31:20 CET [ BibTeX BibTeX for corresponding Paper Download ] 2296 views, 907 downloads, 2 subscriptions

About: This Matlab package implements a method for learning a choquistic regression model (represented by a corresponding Moebius transform of the underlying fuzzy measure), using the maximum likelihood approach proposed in [2], eqquiped by sigmoid normalization, see [1].

Changes:

Initial Announcement on mloss.org.


Logo Blocks 0.1

by bartvm - March 30, 2015, 22:25:02 CET [ Project Homepage BibTeX Download ] 2720 views, 704 downloads, 3 subscriptions

About: A Theano framework for building and training neural networks

Changes:

Initial Announcement on mloss.org.


Logo apsis 0.1.1

by fdiehl - March 17, 2015, 08:27:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3801 views, 731 downloads, 2 subscriptions

About: A toolkit for hyperparameter optimization for machine learning algorithms.

Changes:

Initial Announcement on mloss.org.


Logo Machine Learning Support System MALSS 0.5.0

by canard0328 - February 20, 2015, 15:56:02 CET [ Project Homepage BibTeX Download ] 2542 views, 731 downloads, 1 subscription

About: MALSS is a python module to facilitate machine learning tasks.

Changes:

Initial Announcement on mloss.org.


About: Learns dynamic network changes across conditions and visualize the results in Cytoscape.

Changes:

Initial Announcement on mloss.org.


Logo Hub Miner 1.1

by nenadtomasev - January 22, 2015, 16:33:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5934 views, 1031 downloads, 2 subscriptions

About: Hubness-aware Machine Learning for High-dimensional Data

Changes:
  • BibTex support for all algorithm implementations, making all of them easy to reference (via algref package).

  • Two more hubness-aware approaches (meta-metric-learning and feature construction)

  • An implementation of Hit-Miss networks for analysis.

  • Several minor bug fixes.

  • The following instance selection methods were added: HMScore, Carving, Iterative Case Filtering, ENRBF.

  • The following clustering quality indexes were added: Folkes-Mallows, Calinski-Harabasz, PBM, G+, Tau, Point-Biserial, Hubert's statistic, McClain-Rao, C-root-k.

  • Some more experimental scripts have been included.

  • Extensions in the estimation of hubness risk.

  • Alias and weighted reservoir methods for weight-proportional random selection.


Logo gaml 1.10

by frezza - January 8, 2015, 14:06:58 CET [ Project Homepage BibTeX Download ] 2689 views, 769 downloads, 2 subscriptions

About: C++ generic programming tools for machine learning

Changes:

Initial Announcement on mloss.org.


Logo JEMLA 1.0

by bathaeian - January 4, 2015, 08:34:49 CET [ Project Homepage BibTeX Download ] 2546 views, 789 downloads, 3 subscriptions

About: Java package for calculating Entropy for Machine Learning Applications. It has implemented several methods of handling missing values. So it can be used as a lab for examining missing values.

Changes:

Discretizing numerical values is added to calculate mode of values and fractional replacement of missing ones. class diagram is on the web http://profs.basu.ac.ir/bathaeian/free_space/jemla.rar


Logo pySPACE 1.2

by krell84 - October 29, 2014, 15:36:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8214 views, 1535 downloads, 1 subscription

About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.

Changes:

improved testing, improved documentation, windows compatibility, more algorithms


Logo RankSVM NC 1.0

by rflamary - July 10, 2014, 15:51:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5254 views, 1268 downloads, 1 subscription

About: This package is an implementation of a linear RankSVM solver with non-convex regularization.

Changes:

Initial Announcement on mloss.org.


Logo PredictionIO 0.7.0

by simonc - April 29, 2014, 20:59:57 CET [ Project Homepage BibTeX Download ] 15862 views, 3289 downloads, 2 subscriptions

About: Open Source Machine Learning Server

Changes:
  • Single machine version for small-to-medium scale deployments
  • Integrated GraphChi (disk-based large-scale graph computation) and algorithms: ALS, CCD++, SGD, CLiMF
  • Improved runtime for training and offline evaluation
  • Bug fixes

See release notes - https://predictionio.atlassian.net/secure/ReleaseNote.jspa?projectId=10000&version=11801


Logo JMLR fastclime 1.2.3

by colin1898 - March 10, 2014, 08:54:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6604 views, 1878 downloads, 1 subscription

About: The package "fastclime" provides a method of recover the precision matrix efficiently by applying parametric simplex method. The computation is based on a linear optimization solver. It also contains a generic LP solver and a parameterized LP solver using parametric simplex method.

Changes:

Initial Announcement on mloss.org.


Logo The Choquet Kernel 1.00

by AliFall - February 11, 2014, 16:21:15 CET [ BibTeX BibTeX for corresponding Paper Download ] 2924 views, 962 downloads, 1 subscription

About: The package computes the optimal parameters for the Choquet kernel

Changes:

Initial Announcement on mloss.org.


Logo jackstraw 1.0

by nc - February 1, 2014, 22:53:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4029 views, 885 downloads, 1 subscription

About: Estimates statistical significance of association between variables and their principal components (PCs).

Changes:

Initial Announcement on mloss.org.


Logo Ordinal Choquistic Regression 1.00

by AliFall - January 30, 2014, 15:42:34 CET [ BibTeX BibTeX for corresponding Paper Download ] 2860 views, 864 downloads, 1 subscription

About: "Ordinal Choquistic Regression" model using the maximum likelihood

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 ] 13848 views, 2734 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


Showing Items 21-40 of 69 on page 2 of 4: Previous 1 2 3 4 Next