Projects running under windows.
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Logo WEKA 3.9.2

by mhall - December 22, 2017, 03:39:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 79947 views, 17992 downloads, 5 subscriptions

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About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...]

Changes:

This release include a lot of bug fixes and improvements. Some of these are detailed at

http://jira.pentaho.com/projects/DATAMINING/issues/DATAMINING-771

As usual, for a complete list of changes refer to the changelogs.


Logo JMLR dlib ml 19.8

by davis685 - December 20, 2017, 03:29:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 211284 views, 32700 downloads, 5 subscriptions

About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.

Changes:

This release includes a lot of bug fixes, usability enhancements, and speedups. It also includes a new global optimization algorithm as well as new examples showing how to do semantic segmentation using dlib's deep learning tooling.


Logo Operator Discretization Library 0.6

by jonasadl - December 19, 2017, 15:24:08 CET [ Project Homepage BibTeX Download ] 389 views, 114 downloads, 2 subscriptions

About: Operator Discretization Library (ODL) is a Python library that enables research in inverse problems on realistic or real data.

Changes:

Initial Announcement on mloss.org.


Logo sparkcrowd 0.1.5

by enriquegrodrigo - December 13, 2017, 13:13:35 CET [ Project Homepage BibTeX Download ] 1186 views, 366 downloads, 3 subscriptions

About: A Spark package implementing algorithms for learning from crowdsourced big data.

Changes:

Changes: - Minor improvements in code and documentation


Logo Theano 1.0.1

by jaberg - December 7, 2017, 14:14:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 39694 views, 6745 downloads, 3 subscriptions

About: A Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Dynamically generates CPU and GPU modules for good performance. Deep Learning Tutorials illustrate deep learning with Theano.

Changes:

Theano 1.0.1 (6th of December, 2017)

This is a maintenance release of Theano, version 1.0.1, with no new features, but some important bug fixes.

Highlights (since 1.0.0):

  • Fixed compilation and improved float16 support for topK on GPU

  • NB: topK support on GPU is experimental and may not work for large input sizes on certain GPUs

  • Fixed cuDNN reductions when axes to reduce have size 1

  • Attempted to prevent re-initialization of the GPU in a child process

  • Fixed support for temporary paths with spaces in Theano initialization

  • Spell check pass on the documentation


Logo MLweb 1.1

by lauerfab - November 10, 2017, 11:34:48 CET [ Project Homepage BibTeX Download ] 13505 views, 3214 downloads, 3 subscriptions

About: MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side. It includes (i) a javascript library to enable scientific computing within web pages, (ii) a javascript library implementing machine learning algorithms for classification, regression, clustering and dimensionality reduction, (iii) a web application providing a matlab-like development environment.

Changes:
  • Add gaxpy() and documentation on in-place operations
  • Add loo() function to Classifier and Regression models
  • New contributed toolbox for RNN
  • Minor fixes

Logo AffectiveTweets 1.0.0

by felipebravom - November 1, 2017, 02:24:58 CET [ Project Homepage BibTeX Download ] 711 views, 234 downloads, 3 subscriptions

About: A WEKA package for analyzing emotion and sentiment of tweets.

Changes:

Initial Announcement on mloss.org.


Logo Accord.NET Framework 3.8.0

by cesarsouza - October 23, 2017, 20:50:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 42950 views, 7232 downloads, 2 subscriptions

About: The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details.

Changes:

For a complete list of changes, please see the full release notes at the release details page at:

https://github.com/accord-net/framework/releases/tag/v3.8.0


Logo JMLR Jstacs 2.3

by keili - September 13, 2017, 14:25:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 33315 views, 7644 downloads, 4 subscriptions

About: A Java framework for statistical analysis and classification of biological sequences

Changes:

New classes and packages:

  • Jstacs 2.3 is the first release to be accompanied by JstacsFX, a library for building JavaFX-based graphical user interfaces based on JstacsTools
  • new interface MultiThreadedFunction
  • new class LargeSequenceReader for reading large sequence files in chunks
  • new interface QuickScanningSequenceScore
  • new class RegExpValidator for checking String inputs against a regular expression
  • new class IUPACDNAAlphabet

New features and improvements:

  • Alignments may now handle different costs for insert and delete gaps
  • ListResults may now be constructed from Collections of ResultSets
  • Several minor improvements and bugfixes in many classes
  • Improvements of documentation of several classes

About: A non-iterative, incremental and hyperparameter-free learning method for one-layer feedforward neural networks without hidden layers. This method efficiently obtains the optimal parameters of the network, regardless of whether the data contains a greater number of samples than variables or vice versa. It does this by using a square loss function that measures errors before the output activation functions and scales them by the slope of these functions at each data point. The outcome is a system of linear equations that obtain the network's weights and that is further transformed using Singular Value Decomposition.

Changes:

Initial Announcement on mloss.org.


About: A non-iterative learning method for one-layer (no hidden layer) neural networks, where the weights can be calculated in a closed-form manner, thereby avoiding low convergence rate and also hyperparameter tuning. The proposed learning method, LANN-SVD in short, presents a good computational efficiency for large-scale data analytic.

Changes:

Initial Announcement on mloss.org.


Logo Somoclu 1.7.4

by peterwittek - June 6, 2017, 15:48:11 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 35053 views, 6299 downloads, 3 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, Julia, R, and MATLAB are supported.

Changes:
  • New: Verbosity parameter in the command-line, Python, MATLAB, and Julia interfaces.
  • Changed: Calculation of U-matrix parallelized.
  • Changed: Moved feeding data to train method in the Python interface.
  • Fixed: The random seed was set to 0 for testing purposes. This is now changed to a wall-time based initialization.
  • Fixed: Sparse matrix reader made more robust.
  • Fixed: Compatibility with kohonen 3 resolved.
  • Fixed: Compatibility with Matplotlib 2 resolved.

Logo JMLR MSVMpack 1.5.1

by lauerfab - March 9, 2017, 12:29:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 32389 views, 9199 downloads, 2 subscriptions

About: MSVMpack is a Multi-class Support Vector Machine (M-SVM) package. It is dedicated to SVMs which can handle more than two classes without relying on decomposition methods and implements the four M-SVM models from the literature: Weston and Watkins M-SVM, Crammer and Singer M-SVM, Lee, Lin and Wahba M-SVM, and the M-SVM2 of Guermeur and Monfrini.

Changes:
  • Fix compilation error with recent gcc

Logo Armadillo library 7.800

by cu24gjf - March 8, 2017, 10:11:25 CET [ Project Homepage BibTeX Download ] 126529 views, 24106 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:
  • more accurate sparse eigen decomposition by eigs_sym() and eigs_gen()
  • more robust handling of non-square matrices by lu()
  • expanded qz() to optionally specify ordering of the Schur form
  • expanded .each_slice() in the Cube class to support matrix multiplication
  • expanded several functions to handle sparse matrices
  • added expmat_sym(), logmat_sympd(), sqrtmat_sympd() for handling symmetric matrices
  • added polyfit() and polyval() for polynomial fitting
  • fix for aliasing issue in convolution functions conv() and conv2()
  • fix for memory leak in the field class when compiling in C++11/C++14 mode

Logo OpenNN 3.1

by Sergiointelnics - March 3, 2017, 17:17:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12840 views, 1957 downloads, 4 subscriptions

About: OpenNN is a software library written in C++ for advanced analytics. It implements neural networks, the most successful machine learning method. The library has been designed to learn from both data sets and mathematical models.

Changes:

New algorithms, correction of bugs.


Logo MIToolbox 3.0.1

by apocock - March 2, 2017, 00:38:52 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 38028 views, 6324 downloads, 3 subscriptions

About: A mutual information library for C and Mex bindings for MATLAB. Aimed at feature selection, and provides simple methods to calculate mutual information, conditional mutual information, entropy, conditional entropy, Renyi entropy/mutual information, and weighted variants of Shannon entropies/mutual informations. Works with discrete distributions, and expects column vectors of features.

Changes:

Fixed a Windows compilation bug. MIToolbox v3 should now compile using Visual Studio.


Logo opusminer 0.1-0

by opusminer - February 23, 2017, 01:01:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1716 views, 291 downloads, 3 subscriptions

About: The new R package opusminer provides an R interface to the OPUS Miner algorithm (implemented in C++) for finding the key associations in transaction data efficiently, in the form of self-sufficient itemsets, using either leverage or lift.

Changes:

Initial Announcement on mloss.org.


Logo Bagging PCA Hashing 1.0

by openpr_nlpr - February 6, 2017, 10:38:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1810 views, 259 downloads, 3 subscriptions

About: The proposed hashing algorithm leverages the bootstrap sampling idea and integrates it with PCA, resulting in a new projection method called Bagging PCA Hashing.

Changes:

Initial Announcement on mloss.org.


Logo Online Sketching Hashing 1.0

by openpr_nlpr - February 6, 2017, 10:36:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1578 views, 205 downloads, 3 subscriptions

About: This is an online hashing algorithm which can handle the stream data with low computational cost.

Changes:

Initial Announcement on mloss.org.


Logo LogRegCrowds, Logistic Regression from Crowds 1.0

by fmpr - January 16, 2017, 18:10:57 CET [ Project Homepage BibTeX Download ] 4753 views, 1190 downloads, 3 subscriptions

About: LogReg-Crowds is a collection of Julia implementations of various approaches for learning a logistic regression model multiple annotators and crowds, namely the works of Raykar et al. (2010), Rodrigues et al. (2013) and Dawid and Skene (1979).

Changes:

Initial Announcement on mloss.org. Added GitHub page.


Showing Items 1-20 of 213 on page 1 of 11: 1 2 3 4 5 6 Next Last