Projects supporting the matlab data format.
Showing Items 1-20 of 72 on page 1 of 4: 1 2 3 4 Next

Logo slim for matlab 0.2

by ustunb - August 23, 2016, 20:27:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 955 views, 126 downloads, 2 subscriptions

About: learn optimized scoring systems using MATLAB and the CPLEX Optimization Studio

Changes:

Initial Announcement on mloss.org.


Logo NaN toolbox 3.0.3

by schloegl - August 19, 2016, 11:08:57 CET [ Project Homepage BibTeX Download ] 49871 views, 10041 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.3.0.3 - 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 Social Impact theory based Optimizer library 1.1

by rishem - July 29, 2016, 13:19:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8115 views, 1641 downloads, 2 subscriptions

About: This is an optimization library based on Social Impact Theory(SITO). The optimizer works in the same way as PSO and GA.

Changes:

bug removed


About: Nowadays this is very popular to use the deep architectures in machine learning. Deep Belief Networks (DBNs) are deep architectures that use a stack of Restricted Boltzmann Machines (RBM) to create a powerful generative model using training data. DBNs have many abilities such as feature extraction and classification that are used in many applications including image processing, speech processing, text categorization, etc. This paper introduces a new object oriented toolbox with the most important abilities needed for the implementation of DBNs. According to the results of the experiments conducted on the MNIST (image), ISOLET (speech), and the 20 Newsgroups (text) datasets, it was shown that the toolbox can learn automatically a good representation of the input from unlabeled data with better discrimination between different classes. Also on all the aforementioned datasets, the obtained classification errors are comparable to those of the state of the art classifiers. In addition, the toolbox supports different sampling methods (e.g. Gibbs, CD, PCD and our new FEPCD method), different sparsity methods (quadratic, rate distortion and our new normal method), different RBM types (generative and discriminative), GPU based, etc. The toolbox is a user-friendly open source software in MATLAB and Octave and is freely available on the website.

Changes:

New in toolbox

  • Using GPU in Backpropagation
  • Revision of some demo scripts
  • Function approximation with multiple outputs
  • Feature extraction with GRBM in first layer

cardinal


Logo JMLR Information Theoretical Estimators 0.63

by szzoli - June 9, 2016, 23:42:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 109825 views, 20674 downloads, 3 subscriptions

About: ITE (Information Theoretical Estimators) is capable of estimating many different variants of entropy, mutual information, divergence, association measures, cross quantities and kernels on distributions. Thanks to its highly modular design, ITE supports additionally (i) the combinations of the estimation techniques, (ii) the easy construction and embedding of novel information theoretical estimators, and (iii) their immediate application in information theoretical optimization problems.

Changes:
  • Conditional Shannon entropy estimation: added.

  • Conditional Shannon mutual information estimation: included.


Logo JMLR GPstuff 4.7

by avehtari - June 9, 2016, 17:45:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 35797 views, 8637 downloads, 3 subscriptions

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About: The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods.

Changes:

2016-06-09 Version 4.7

Development and release branches available at https://github.com/gpstuff-dev/gpstuff

New features

  • Simple Bayesian Optimization demo

Improvements

  • Improved use of PSIS
  • More options added to gp_monotonic
  • Monotonicity now works for additive covariance functions with selected variables
  • Possibility to use gpcf_squared.m-covariance function with derivative observations/monotonicity
  • Default behaviour made more robust by changing default jitter from 1e-9 to 1e-6
  • LA-LOO uses the cavity method as the default (see Vehtari et al (2016). Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models. JMLR, accpeted for publication)
  • Selected variables -option works now better with monotonicity

Bugfixes

  • small error in derivative observation computation fixed
  • several minor bug fixes

Logo FEAST 1.1.4

by apocock - March 12, 2016, 18:35:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 37052 views, 6861 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:
  • Fixed an issue where zero MI values would cause it to segfault.
  • Fixes to documentation and comments.
  • Updated internal version of MIToolbox.

Logo MDLText 1

by renatoms88 - March 3, 2016, 19:31:25 CET [ BibTeX Download ] 611 views, 229 downloads, 2 subscriptions

About: testing mloss.org

Changes:

Initial Announcement on mloss.org.


Logo Local high order regularization 1.0

by kkim - March 2, 2016, 13:46:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1031 views, 253 downloads, 2 subscriptions

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About: Local high-order regularization for semi-supervised learning

Changes:

Initial Announcement on mloss.org.


Logo MIToolbox 2.1.2

by apocock - January 10, 2016, 22:19:30 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 27551 views, 4750 downloads, 2 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:

Relicensed as BSD. Added checks to catch MATLAB inputs that aren't doubles.


Logo Sparse PCA 2.0

by tbuehler - December 31, 2015, 16:24:42 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6134 views, 1448 downloads, 3 subscriptions

About: A Matlab implementation of Sparse PCA using the inverse power method for nonlinear eigenproblems.

Changes:
  • Added deflation scheme to compute multiple principal components
  • Several internal runtime and memory optimizations
  • API change: sparsePCA.m is now used to compute multiple components; use computeTradeOffCurve.m to reproduce the examples in the NIPS paper

Logo A Pattern Recognizer In Lua with ANNs v0.4.1

by pakozm - December 3, 2015, 15:01:36 CET [ Project Homepage BibTeX Download ] 8029 views, 1817 downloads, 2 subscriptions

About: APRIL-ANN toolkit (A Pattern Recognizer In Lua with Artificial Neural Networks). This toolkit incorporates ANN algorithms (as dropout, stacked denoising auto-encoders, convolutional neural networks), with other pattern recognition methods as hidden makov models (HMMs) among others.

Changes:
  • Updated home repository link to follow april-org github organization.
  • Improved serialize/deserialize functions, reimplemented all the serialization procedure.
  • Added exceptions support to LuaPkg and APRIL-ANN, allowing to capture C++ errors into Lua code.
  • Added set class.
  • Added series class.
  • Added data_frame class, similar to Python Pandas DataFrame.
  • Serialization and deserilization have been updated with more robust and reusable API, implemented in util.serialize() and util.deserialize() functions.
  • Added matrix.ext.broadcast utility (similar to broadcast in numpy).
  • Added ProbablisitcMatrixANNComponent, which allow to implement probabilistic mixtures of posteriors and/or likelihoods.
  • Added batch normalization ANN component.
  • Allowing matrix.join to add new axis.
  • Added methods prod(), cumsum() and cumprod() at matrix classes.
  • Added methods count_eq() and count_neq() at matrix classes.
  • Serializable objects API have been augmented with methods ctor_name() and
    ctor_params() in Lua, refered to luaCtorName() and luaCtorParams() in C++.
  • Added cast.to to dynamic cast C++ objects pushed into Lua, allowing to convert base class objects into any of its derived classes.
  • Added matrix.sparse as valid values for targets in ann.loss.mse and
    ann.loss.cross_entropy.
  • Changed matrix metamethods __index and __newindex, allowing to use
    matrix objects with standard Lua operator[].
  • Added matrix.masked_fill and matrix.masked_copy matrix.
  • Added matrix.indexed_fill and matrix.indexed_copy matrix.
  • Added ann.components.probabilistic_matrix, and its corresponding specializations ann.components.left_probabilistic_matrix and
    ann.components.right_probabilistic_matrix.
  • Added operator[] in the right side of matrix operations.
  • Added ann.components.transpose.
  • Added max_gradients_norm in traianble.supervised_trainer, to avoid gradients exploding.
  • Added ann.components.actf.sparse_logistic a logistic activation function with sparsity penalty.
  • Simplified math.add, math.sub, ... and other math extensions for reductions, their original behavior can be emulated by using bind function.
  • Added bind function to freeze any positional argument of any Lua function.
  • Function stats.boot uses multiple_unpack to allow a table of sizes and the generation of multiple index matrices.
  • Added multiple_unpack Lua function.
  • Added __tostring metamethod to numeric memory blocks in Lua.
  • Added dataset.token.sparse_matrix, a dataset which allow to traverse by rows a sparse matrix instance.
  • Added matrix.sparse.builders.dok, a builder which uses the Dictionary-of-Keys format to construct a sparse matrix from scratch.
  • Added method data to numeric matrix classes.
  • Added methods values, indices, first_index to sparse matrix class.
  • Fixed bugs when reading bad formed CSV files.
  • Fixed bugs at statistical distributions.
  • FloatRGB bug solved on equal (+=, -=, ...) operators. This bug affected ImageRGB operations such as resize.
  • Solved problems when chaining methods in Lua, some objects end to be garbage collected.
  • Improved support of strings in auto-completion (rlcompleter package).
  • Solved bug at SparseMatrix<T> when reading it from a file.
  • Solved bug in Image<T>::rotate90_cw methods.
  • Solved bug in SparseMatrix::toDense() method.

C/C++

  • Better LuaTable accessors, using [] operator.
  • Implementation of matrix __index, __newindex and __call metamethods in C++.
  • Implementation of matProd(), matCumSum() and matCumProd() functions.
  • Implementation of matCountEq() and matCountNeq() functions for
    Matrix<T>.
  • Updated matrix_ext_operations.h to change API of matrix operations. All functions have been overloaded to accept an in-place operation and another version which receives a destination matrix.
  • Adding iterators to language models.
  • Added MatrixScalarMap2 which receives as input2 a SparaseMatrix instance. This functions needs to be generalized to work with CPU and CUDA.
  • The method SparseMatrix<T>::fromDenseMatrix() uses a DOKBuilder object to build the sparse matrix.
  • The conversion of a Matrix<T> into a SparseMatrix<T> has been changed from a constructor overload to the static method
    SparseMatrix<T>::fromDenseMatrix().
  • Added support for IPyLua.
  • Optimized matrix access for confusion matrix.
  • Minor changes in class.lua.
  • Improved binding to avoid multiple object copies when pushing C++ objects.
  • Added Git commit hash and compilation time.

Logo A Library for Online Streaming Feature Selection 1.0

by ykui713 - November 25, 2015, 13:23:01 CET [ BibTeX Download ] 992 views, 395 downloads, 1 subscription

About: LOFS is a software toolbox for online streaming feature selection

Changes:

Initial Announcement on mloss.org.


Logo Cognitive Foundry 3.4.2

by Baz - October 30, 2015, 06:53:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 28928 views, 4930 downloads, 4 subscriptions

About: The Cognitive Foundry is a modular Java software library of machine learning components and algorithms designed for research and applications.

Changes:
  • General:
    • Upgraded MTJ to 1.0.3.
  • Common:
    • Added package for hash function computation including Eva, FNV-1a, MD5, Murmur2, Prime, SHA1, SHA2
    • Added callback-based forEach implementations to Vector and InfiniteVector, which can be faster for iterating through some vector types.
    • Optimized DenseVector by removing a layer of indirection.
    • Added method to compute set of percentiles in UnivariateStatisticsUtil and fixed issue with percentile interpolation.
    • Added utility class for enumerating combinations.
    • Adjusted ScalarMap implementation hierarchy.
    • Added method for copying a map to VectorFactory and moved createVectorCapacity up from SparseVectorFactory.
    • Added method for creating square identity matrix to MatrixFactory.
    • Added Random implementation that uses a cached set of values.
  • Learning:
    • Implemented feature hashing.
    • Added factory for random forests.
    • Implemented uniform distribution over integer values.
    • Added Chi-squared similarity.
    • Added KL divergence.
    • Added general conditional probability distribution.
    • Added interfaces for Regression, UnivariateRegression, and MultivariateRegression.
    • Fixed null pointer exception that can happen in K-means with an empty cluster.
    • Fixed name of maxClusters property on AgglomerativeClusterer (was called maxMinDistance).
  • Text:
    • Improvements to LDA Gibbs sampler.

Logo Chalearn gesture challenge code by jun wan 2.0

by joewan - September 29, 2015, 08:50:22 CET [ BibTeX BibTeX for corresponding Paper Download ] 6353 views, 1507 downloads, 2 subscriptions

About: This code is provided by Jun Wan. It is used in the Chalearn one-shot learning gesture challenge (round 2). This code includes: bag of features, 3D MoSIFT-based features (i.e. 3D MoSIFT, 3D EMoSIFT and 3D SMoSIFT), and the MFSK feature.

Changes:

Initial Announcement on mloss.org.


Logo Universal Java Matrix Package 0.3.0

by arndt - July 31, 2015, 14:23:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14237 views, 2717 downloads, 3 subscriptions

About: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multi-threading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more.

Changes:

Updated to version 0.3.0


Logo JMLR GPML Gaussian Processes for Machine Learning Toolbox 3.6

by hn - July 6, 2015, 12:31:28 CET [ Project Homepage BibTeX Download ] 36111 views, 8245 downloads, 4 subscriptions

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About: The GPML toolbox is a flexible and generic Octave 3.2.x and Matlab 7.x implementation of inference and prediction in Gaussian Process (GP) models.

Changes:
  • added a new inference function infGrid_Laplace allowing to use non-Gaussian likelihoods for large grids

  • fixed a bug due to Octave evaluating norm([]) to a tiny nonzero value, modified all lik/lik*.m functions reported by Philipp Richter

  • small bugfixes in covGrid and infGrid

  • bugfix in predictive variance of likNegBinom due to Seth Flaxman

  • bugfix in infFITC_Laplace as suggested by Wu Lin

  • bugfix in covPP{iso,ard}


Logo ABACOC Adaptive Ball Cover for Classification 2.0

by kikot - May 29, 2015, 11:57:28 CET [ BibTeX BibTeX for corresponding Paper Download ] 4776 views, 1204 downloads, 3 subscriptions

About: Incremental (Online) Nonparametric Classifier. You can classify both points (standard) or matrices (multivariate time series). Java and Matlab code already available.

Changes:

version 2: parameterless system, constant model size, prediction confidence (for active learning).

NEW!! C++ version at: https://github.com/ilaria-gori/ABACOC


Logo JMLR Sally 1.0.0

by konrad - March 26, 2015, 17:01:35 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 41560 views, 7990 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 Accord.NET Framework 2.14.0

by cesarsouza - December 9, 2014, 23:04:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 31199 views, 5688 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:

Adding a large number of new distributions, such as Anderson-Daring, Shapiro-Wilk, Inverse Chi-Square, Lévy, Folded Normal, Shifted Log-Logistic, Kumaraswamy, Trapezoidal, U-quadratic and BetaPrime distributions, Birnbaum-Saunders, Generalized Normal, Gumbel, Power Lognormal, Power Normal, Triangular, Tukey Lambda, Logistic, Hyperbolic Secant, Degenerate and General Continuous distributions.

Other additions include new statistical hypothesis tests such as Anderson-Daring and Shapiro-Wilk; as well as support for all of LIBLINEAR's support vector machine algorithms; and format reading support for MATLAB/Octave matrices, LibSVM models, sparse LibSVM data files, and many others.

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


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