Projects running under linux.
Showing Items 1-20 of 271 on page 1 of 14: 1 2 3 4 5 6 Next Last

Logo Somoclu 1.7.4

by peterwittek - June 6, 2017, 15:48:11 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 27669 views, 5016 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 MLweb 0.1.6

by lauerfab - June 1, 2017, 11:48:19 CET [ Project Homepage BibTeX Download ] 9107 views, 2111 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 support for complex numbers, vectors and matrices
  • Add basic signal processing (discrete Fourier transform, sound())
  • Add quadratic discriminant analysis
  • Faster Cholesky factorization

Logo Theano 0.9.0

by jaberg - April 10, 2017, 20:30:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 33145 views, 5569 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 0.9.0 (20th of March, 2017)

Highlights (since 0.8.0):

* Better Python 3.5 support
* Better numpy 1.12 support
* Conda packages for Mac, Linux and Windows
* Support newer Mac and Windows versions
* More Windows integration:

    * Theano scripts (``theano-cache`` and ``theano-nose``) now works on Windows
    * Better support for Windows end-lines into C codes
    * Support for space in paths on Windows

* Scan improvements:

    * More scan optimizations, with faster compilation and gradient computation
    * Support for checkpoint in scan (trade off between speed and memory usage, useful for long sequences)
    * Fixed broadcast checking in scan

* Graphs improvements:

    * More numerical stability by default for some graphs
    * Better handling of corner cases for theano functions and graph optimizations
    * More graph optimizations with faster compilation and execution
    * smaller and more readable graph

* New GPU back-end:

    * Removed warp-synchronous programming to get good results with newer CUDA drivers
    * More pooling support on GPU when cuDNN isn't available
    * Full support of ignore_border option for pooling
    * Inplace storage for shared variables
    * float16 storage
    * Using PCI bus ID of graphic cards for a better mapping between theano device number and nvidia-smi number
    * Fixed offset error in ``GpuIncSubtensor``

* Less C code compilation
* Added support for bool dtype
* Updated and more complete documentation
* Bug fixes related to merge optimizer and shape inference
* Lot of other bug fixes, crashes fixes and warning improvements

Logo JMLR MSVMpack 1.5.1

by lauerfab - March 9, 2017, 12:29:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 27748 views, 8096 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 ] 109992 views, 21648 downloads, 5 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarEmpty Star
(based on 3 votes)

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 ] 9736 views, 1650 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 ] 33885 views, 5667 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 ] 883 views, 143 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 JMLR dlib ml 19.3

by davis685 - February 22, 2017, 04:37:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 183537 views, 28936 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 adds a number of new features, most notably new deep learning tools including a state-of-the-art face recognition example using dlib's deep learning API. See http://dlib.net/dnn_face_recognition_ex.cpp.html for an introduction.


Logo ADENINE 0.1.4

by samuelefiorini - February 17, 2017, 14:50:49 CET [ Project Homepage BibTeX Download ] 2124 views, 489 downloads, 2 subscriptions

About: ADENINE (A Data ExploratioN pIpeliNE) is a machine learning framework for data exploration that encompasses state-of-the-art techniques for missing values imputing, data preprocessing, unsupervised feature learning and clustering tasks.

Changes:
  • Adenine can now distribute the execution of its pipelines on multiple machines via MPI
  • kNN data imputing strategy is now implemented
  • added python 2.7 and 3.5 support
  • stability improved and bug fixed

Logo LogRegCrowds, Logistic Regression from Crowds 1.0

by fmpr - January 16, 2017, 18:10:57 CET [ Project Homepage BibTeX Download ] 3588 views, 935 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.


Logo Multi Annotator Supervised LDA for regression 1.0

by fmpr - January 16, 2017, 18:10:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1302 views, 192 downloads, 3 subscriptions

About: MA-sLDAr is a C++ implementation of the supervised topic models with response variables provided by multiple annotators with different levels of expertise.

Changes:

Initial Announcement on mloss.org.


Logo Multi Annotator Supervised LDA for classification 1.0

by fmpr - January 16, 2017, 18:01:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1080 views, 159 downloads, 3 subscriptions

About: MA-sLDAc is a C++ implementation of the supervised topic models with labels provided by multiple annotators with different levels of expertise.

Changes:

Initial Announcement on mloss.org.


Logo Java Statistical Analysis Tool 0.0.7

by EdwardRaff - January 15, 2017, 22:21:50 CET [ Project Homepage BibTeX Download ] 2930 views, 711 downloads, 2 subscriptions

About: General purpose Java Machine Learning library for classification, regression, and clustering.

Changes:

See github release tab for change info


Logo FEAST 2.0.0

by apocock - January 8, 2017, 00:49:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 45280 views, 8002 downloads, 3 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarWhole Star
(based on 2 votes)

About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab.

Changes:

Major refactoring of FEAST to improve speed and portability.

  • FEAST now clones the input data if it's floating point and discretises it to unsigned ints once in a single pass. This improves the speed by about 30%.
  • FEAST now has unsigned int entry points which avoid this discretisation and are much faster if the data is already categorical.
  • Added weighted feature selection algorithms to FEAST which can be used for cost-sensitive feature selection.
  • Added a Java API using JNI.
  • FEAST now returns the internal score for each feature according to the criterion. Available in all three APIs.
  • Rearranged the repository to make it easier to work with. Header files are now in `include`, source in `src`, the MATLAB API is in `matlab/` and the Java API is in `java/`.
  • FEAST now compiles cleanly using `-std=c89 -Wall -Werror`.

About: Hierarchical Recurrent Neural Network for Skeleton Based Action Recognition

Changes:

Initial Announcement on mloss.org.


Logo WEKA 3.9.1

by mhall - December 19, 2016, 04:44:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 71454 views, 13163 downloads, 5 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarEmpty Star
(based on 6 votes)

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:

In core weka:

  • JAMA-based linear algebra routines replaced with MTJ. Faster operation with the option to use native libraries for even more speed
  • General efficiency improvements in core, filters and some classifiers
  • GaussianProcesses now handles instance weights
  • New Knowledge Flow implementation. Engine completely rewritten from scratch with a simplified API
  • New Workbench GUI
  • GUI package manager now has a search facility
  • FixedDictionaryStringToWordVector filter allows the use of an external dictionary for vectorization. DictionarySaver converter can be used to create a dictionary file

In packages:

  • Packages that were using JAMA are now using MTJ
  • New netlibNativeOSX, netlibNativeWindows and netlibNativeLinux packages providing native reference implementations (and system-optimized implementation in the case of OSX) of BLAS, LAPACK and ARPACK linear algebra
  • New elasticNet package, courtesy of Nikhil Kinshore
  • New niftiLoader package for loading a directory with MIR data in NIfTI format into Weka
  • New percentageErrorMetrics package - provides plugin evaluation metrics for root mean square percentage error and mean absolute percentage error
  • New iterativeAbsoluteErrorRegression package - provides a meta learner that fits a regression model to minimize absolute error
  • New largeScaleKernelLearning package - contains filters for large-scale kernel-based learning
  • discriminantAnalysis package now contains an implementation for LDA and QDA
  • New Knowledge Flow component implementations in various packages
  • newKnowledgeFlowStepExamples package - contains code examples for new Knowledge Flow API discussion in the Weka Manual
  • RPlugin updated to latest version of MLR
  • scatterPlot3D and associationRulesVisualizer packages updated with latest Java 3D libraries
  • Support for pluggable activation functions in the multiLayerPerceptrons package

Logo JMLR scikitlearn 0.18.1

by fabianp - November 28, 2016, 17:45:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 29658 views, 10970 downloads, 5 subscriptions

Rating Whole StarWhole StarWhole StarWhole Star1/2 Star
(based on 3 votes)

About: The scikit-learn project is a machine learning library in Python.

Changes:

Update for 0.18 .1


Logo DIANNE 0.5.0

by sbohez - October 25, 2016, 19:51:07 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1674 views, 309 downloads, 3 subscriptions

About: DIANNE is a modular software framework for designing, training and evaluating artificial neural networks on heterogeneous, distributed infrastructure . It is built on top of OSGi and AIOLOS and can transparently deploy and redeploy (parts of) a neural network on multiple machines, as well as scale up training on a compute cluster.

Changes:

Initial Announcement on mloss.org.


Logo RLScore 0.7

by aatapa - September 20, 2016, 09:51:25 CET [ Project Homepage BibTeX Download ] 1478 views, 355 downloads, 3 subscriptions

About: RLScore - regularized least-squares machine learning algorithms package

Changes:

Initial Announcement on mloss.org.


Showing Items 1-20 of 271 on page 1 of 14: 1 2 3 4 5 6 Next Last