20 projects found that use c as the programming language.
Showing Items 1-20 of 97 on page 1 of 5: 1 2 3 4 5 Next

Logo NaN toolbox 3.1.2

by schloegl - January 22, 2017, 12:24:59 CET [ Project Homepage BibTeX Download ] 54823 views, 11050 downloads, 3 subscriptions

About: NaN-toolbox is a statistics and machine learning toolbox for handling data with and without missing values.

Changes:

Changes in v.3.1.2 - improve configuration and build system - support of more platforms (including Octave 4.2.0) improved

Changes in v.3.0.3 - improve compatibility for Octave on Windows

Changes in v.3.0.1 - fix packaging for octave

Changes in v.2.8.5 - bug fix: trimmean - compiler support for gcc-5 and clang - fix typos

For details see the CHANGELOG at http://pub.ist.ac.at/~schloegl/matlab/NaN/CHANGELOG


Logo FEAST 2.0.0

by apocock - January 8, 2017, 00:49:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 41159 views, 7350 downloads, 3 subscriptions

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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`.

Logo MIToolbox 3.0.0

by apocock - January 8, 2017, 00:43:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30389 views, 5124 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:

Major refactor of code and reorganised the repository so it's a little more sensible.

  • Refactored all C functions to expose a version which takes unsigned integer inputs.
  • Rearranged the repository to separate out headers from source, and MATLAB code from C library code.

Minor changes:

  • General code cleanup to reduce duplicated code.
  • Adding an COMPILE_R flag to go with the COMPILE_C flag, to make it easier to produce an R wrapper.
  • All code now compiles cleanly with "-std=c89 -Wall -Werror".

Logo JMLR scikitlearn 0.18.1

by fabianp - November 28, 2016, 17:45:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 26413 views, 9597 downloads, 5 subscriptions

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

Changes:

Update for 0.18 .1


Logo Salad 0.6.1

by chwress - June 17, 2016, 11:26:34 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13942 views, 2594 downloads, 3 subscriptions

About: A Content Anomaly Detector based on n-Grams

Changes:

A teeny tiny fix to correctly handle input strings shorter than a registers width


Logo hca 0.63

by wbuntine - April 26, 2016, 15:35:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 24764 views, 3398 downloads, 4 subscriptions

About: Multi-core non-parametric and bursty topic models (HDP-LDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls.

Changes:

Corrected the new normalised Gamma model for topics so it works with multicore. Improvements to documentation. Added an asymptotic version of the generalised Stirling numbers so it longer fails when they run out of bounds on bigger data.


Logo Harry 0.4.2

by konrad - April 16, 2016, 10:50:38 CET [ Project Homepage BibTeX Download ] 11087 views, 2387 downloads, 3 subscriptions

About: A Tool for Measuring String Similarity

Changes:

This release fixes the incorrect implementation of the bag distance.


Logo Theano 0.8.1

by jaberg - April 1, 2016, 19:22:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 29359 views, 4961 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 0.8.1 (29th of March, 2016)

* Fix compilation on Mac with CLT 7.3

Theano 0.8 (21th of March, 2016)

We recommend to everyone to upgrade to this version.

Highlights:

* Python 2 and 3 support with the same code base
* Faster optimization
* Integration of CuDNN for better GPU performance
* Many Scan improvements (execution speed up, ...)
* optimizer=fast_compile moves computation to the GPU.
* Better convolution on CPU and GPU. (CorrMM, cudnn, 3d conv, more parameter)
* Interactive visualization of graphs with d3viz
* cnmem (better memory management on GPU)
* BreakpointOp
* Multi-GPU for data parallism via Platoon (https://github.com/mila-udem/platoon/)
* More pooling parameter supported
* Bilinear interpolation of images
* New GPU back-end:

    * Float16 new back-end (need cuda 7.5)
    * Multi dtypes
    * Multi-GPU support in the same process

Logo pattern recognition tool 1.0

by openpr_nlpr - January 19, 2016, 03:54:11 CET [ Project Homepage BibTeX Download ] 1541 views, 386 downloads, 3 subscriptions

About: a tool for marking samples in images for database building, also including algorithm of LBP,HOG,and classifiers of SVM (six kernels), adaboost,BP and convolutional networks, extreme learning machine.

Changes:

Initial Announcement on mloss.org.


Logo BayesOpt, a Bayesian Optimization toolbox 0.8.2

by rmcantin - December 9, 2015, 04:53:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 28383 views, 5271 downloads, 4 subscriptions

About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinear-optimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python.

Changes:

-Fixed bug in save/restore. -Fixed bug in initial design.


Logo Recur 1

by douglasbagnall - June 16, 2015, 12:06:05 CET [ Project Homepage BibTeX Download ] 2050 views, 535 downloads, 2 subscriptions

About: Recur is a collection of Gstreamer plugins and language modelling tools based on recurrent neural networks.

Changes:

Initial Announcement on mloss.org.


Logo GESL v1.01

by bellet - May 15, 2015, 11:54:04 CET [ BibTeX BibTeX for corresponding Paper Download ] 3777 views, 1421 downloads, 1 subscription

About: Learning string edit distance / similarity from data

Changes:

Added datasets used in the experiments of the paper


Logo JMLR Sally 1.0.0

by konrad - March 26, 2015, 17:01:35 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 45618 views, 8663 downloads, 3 subscriptions

About: A Tool for Embedding Strings in Vector Spaces

Changes:

Support for explicit selection of granularity added. Several minor bug fixes. We have reached 1.0


Logo JMLR SHOGUN 4.0.0

by sonne - February 5, 2015, 09:09:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 121009 views, 17136 downloads, 6 subscriptions

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About: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line.

Changes:

This release features the work of our 8 GSoC 2014 students [student; mentors]:

  • OpenCV Integration and Computer Vision Applications [Abhijeet Kislay; Kevin Hughes]
  • Large-Scale Multi-Label Classification [Abinash Panda; Thoralf Klein]
  • Large-scale structured prediction with approximate inference [Jiaolong Xu; Shell Hu]
  • Essential Deep Learning Modules [Khaled Nasr; Sergey Lisitsyn, Theofanis Karaletsos]
  • Fundamental Machine Learning: decision trees, kernel density estimation [Parijat Mazumdar ; Fernando Iglesias]
  • Shogun Missionary & Shogun in Education [Saurabh Mahindre; Heiko Strathmann]
  • Testing and Measuring Variable Interactions With Kernels [Soumyajit De; Dino Sejdinovic, Heiko Strathmann]
  • Variational Learning for Gaussian Processes [Wu Lin; Heiko Strathmann, Emtiyaz Khan]

It also contains several cleanups and bugfixes:

Features

  • New Shogun project description [Heiko Strathmann]
  • ID3 algorithm for decision tree learning [Parijat Mazumdar]
  • New modes for PCA matrix factorizations: SVD & EVD, in-place or reallocating [Parijat Mazumdar]
  • Add Neural Networks with linear, logistic and softmax neurons [Khaled Nasr]
  • Add kernel multiclass strategy examples in multiclass notebook [Saurabh Mahindre]
  • Add decision trees notebook containing examples for ID3 algorithm [Parijat Mazumdar]
  • Add sudoku recognizer ipython notebook [Alejandro Hernandez]
  • Add in-place subsets on features, labels, and custom kernels [Heiko Strathmann]
  • Add Principal Component Analysis notebook [Abhijeet Kislay]
  • Add Multiple Kernel Learning notebook [Saurabh Mahindre]
  • Add Multi-Label classes to enable Multi-Label classification [Thoralf Klein]
  • Add rectified linear neurons, dropout and max-norm regularization to neural networks [Khaled Nasr]
  • Add C4.5 algorithm for multiclass classification using decision trees [Parijat Mazumdar]
  • Add support for arbitrary acyclic graph-structured neural networks [Khaled Nasr]
  • Add CART algorithm for classification and regression using decision trees [Parijat Mazumdar]
  • Add CHAID algorithm for multiclass classification and regression using decision trees [Parijat Mazumdar]
  • Add Convolutional Neural Networks [Khaled Nasr]
  • Add Random Forests algorithm for ensemble learning using CART [Parijat Mazumdar]
  • Add Restricted Botlzmann Machines [Khaled Nasr]
  • Add Stochastic Gradient Boosting algorithm for ensemble learning [Parijat Mazumdar]
  • Add Deep contractive and denoising autoencoders [Khaled Nasr]
  • Add Deep belief networks [Khaled Nasr]

Bugfixes

  • Fix reference counting bugs in CList when reference counting is on [Heiko Strathmann, Thoralf Klein, lambday]
  • Fix memory problem in PCA::apply_to_feature_matrix [Parijat Mazumdar]
  • Fix crash in LeastAngleRegression for the case D greater than N [Parijat Mazumdar]
  • Fix memory violations in bundle method solvers [Thoralf Klein]
  • Fix fail in library_mldatahdf5.cpp example when http://mldata.org is not working properly [Parijat Mazumdar]
  • Fix memory leaks in Vowpal Wabbit, LibSVMFile and KernelPCA [Thoralf Klein]
  • Fix memory and control flow issues discovered by Coverity [Thoralf Klein]
  • Fix R modular interface SWIG typemap (Requires SWIG >= 2.0.5) [Matt Huska]

Cleanup and API Changes

  • PCA now depends on Eigen3 instead of LAPACK [Parijat Mazumdar]
  • Removing redundant and fixing implicit imports [Thoralf Klein]
  • Hide many methods from SWIG, reducing compile memory by 500MiB [Heiko Strathmann, Fernando Iglesias, Thoralf Klein]

About: This library implements the Optimum-Path Forest classifier for unsupervised and supervised learning.

Changes:

Initial Announcement on mloss.org.


Logo CFSPCommunityDetection 1.0

by tbuehler - October 13, 2014, 05:36:24 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2835 views, 724 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo pSpectralClustering 1.1

by tbuehler - July 30, 2014, 19:44:52 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9257 views, 1976 downloads, 2 subscriptions

About: A generalized version of spectral clustering using the graph p-Laplacian.

Changes:
  • fixed compatibility issue with Matlab R2013a+
  • several internal optimizations

Logo QSMM 1.16

by olegvol - July 29, 2014, 19:37:31 CET [ Project Homepage BibTeX Download ] 2338 views, 585 downloads, 3 subscriptions

About: The implementation of adaptive probabilistic mappings.

Changes:

Initial Announcement on mloss.org.


Logo Encog Machine Learning Framework 3.2

by jeffheaton - July 5, 2014, 23:47:06 CET [ Project Homepage BibTeX Download ] 7079 views, 2364 downloads, 1 subscription

About: Encog is a Machine Learning framework for Java, C#, Javascript and C/C++ that supports SVM's, Genetic Programming, Bayesian Networks, Hidden Markov Models and other algorithms.

Changes:

Changes for Encog 3.2:

Issue #53: Fix Out Of Range Bug In BasicMLSequenceSet. Issue #52: Unhandled exception in Encog.Util.File.ResourceLoader.CreateStream (ResourceLoader.cs) Issue #50: Concurrency bugs in PruneIncremental Issue #48: Unit Tests Failing - TestHessian Issue #46: Couple of small fixes - Temporal DataSet and SCG training Issue #45: Fixed EndMinutesStrategy to correctly evaluate ShouldStop after the specified number of minutes have elapsed. Issue #44: Encog.ML.Data.Basic.BasicMLDataPairCentroid.Add() & .Remove() Issue #43: Unit Tests Failing - Matrix not full rank Issue #42: Nuget - NuSpec Issue #36: Load Examples easier


Logo JMLR MSVMpack 1.5

by lauerfab - July 3, 2014, 16:02:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 24589 views, 7441 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:
  • Windows binaries are now included (by Emmanuel Didiot)
  • MSVMpack can now be compiled on Windows (by Emmanuel Didiot)
  • Fixed polynomial kernel
  • Minor bug fixes

Showing Items 1-20 of 97 on page 1 of 5: 1 2 3 4 5 Next