Projects supporting the hdf data format.


Logo Armadillo library 4.400

by cu24gjf - August 20, 2014, 10:15:37 CET [ Project Homepage BibTeX Download ] 41296 views, 9099 downloads, 3 subscriptions

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About: Armadillo is a template C++ linear algebra library aiming towards a good balance between speed and ease of use, with a function syntax similar to MATLAB. Matrix decompositions are provided through optional integration with LAPACK, or one of its high performance drop-in replacements (eg. Intel MKL, OpenBLAS).

Changes:
  • faster handling of aliasing by submatrix views
  • faster handling of subvectors by dot()
  • added clamp() for clamping values to be between lower and upper limits
  • expanded batch insertion constructors for sparse matrices to add values at repeated locations
  • added gmm_diag class for statistical modelling using Gaussian Mixture Models; includes multi-threaded implementation of k-means and Expectation-Maximisation algorithms

Logo BayesPy 0.2

by jluttine - August 14, 2014, 17:24:22 CET [ Project Homepage BibTeX Download ] 1107 views, 324 downloads, 2 subscriptions

About: Variational Bayesian inference tools for Python

Changes:
  • added all common distributions: Poisson, beta, multinomial, Bernoulli, categorical, etc

  • added Gaussian arrays (not just scalars or vectors)

  • added Gaussian Markov chains with time-varying or swithing dynamics

  • added discrete Markov chains (enabling hidden Markov models)

  • added deterministic gating node

  • added deterministic general sum-product node

  • added parameter expansion

  • added new plotting functions: pdf, Hinton diagram

  • added monitoring of posterior distributions during iteration

  • improved documentation


Logo JMLR MLPACK 1.0.9

by rcurtin - July 28, 2014, 20:52:10 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30981 views, 6229 downloads, 6 subscriptions

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About: A scalable, fast C++ machine learning library, with emphasis on usability.

Changes:
  • GMM initialization is now safer and provides a working GMM when constructed with only the dimensionality and number of Gaussians (#314).
  • Check for division by 0 in Forward-Backward Algorithm in HMMs (#314).
  • Fix MaxVarianceNewCluster (used when re-initializing clusters for k-means) (#314).
  • Fixed implementation of Viterbi algorithm in HMM::Predict() (#316).
  • Significant speedups for dual-tree algorithms using the cover tree (#243, #329) including a faster implementation of FastMKS.
  • Fix for LRSDP optimizer so that it compiles and can be used (#325).
  • CF (collaborative filtering) now expects users and items to be zero-indexed, not one-indexed (#324).
  • CF::GetRecommendations() API change: now requires the number of recommendations as the first parameter. The number of users in the local neighborhood should be specified with CF::NumUsersForSimilarity().
  • Removed incorrect PeriodicHRectBound (#30).
  • Refactor LRSDP into LRSDP class and standalone function to be optimized (#318).
  • Fix for centering in kernel PCA (#355).
  • Added simulated annealing (SA) optimizer, contributed by Zhihao Lou.
  • HMMs now support initial state probabilities; these can be set in the constructor, trained, or set manually with HMM::Initial() (#315).
  • Added Nyström method for kernel matrix approximation by Marcus Edel.
  • Kernel PCA now supports using Nyström method for approximation.
  • Ball trees now work with dual-tree algorithms, via the BallBound<> bound structure (#320); fixed by Yash Vadalia.
  • The NMF class is now AMF<>, and supports far more types of factorizations, by Sumedh Ghaisas.
  • A QUIC-SVD implementation has returned, written by Siddharth Agrawal and based on older code from Mudit Gupta.
  • Added perceptron and decision stump by Udit Saxena (these are weak learners for an eventual AdaBoost class).
  • Sparse autoencoder added by Siddharth Agrawal.

Logo JMLR SHOGUN 3.2.0

by sonne - February 17, 2014, 20:31:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 82615 views, 11431 downloads, 5 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 is mostly a bugfix release:

Features

  • Fully support python3 now
  • Add mini-batch k-means [Parijat Mazumdar]
  • Add k-means++ [Parijat Mazumdar]
  • Add sub-sequence string kernel [lambday]

Bugfixes

  • Compile fixes for upcoming swig3.0
  • Speedup for gaussian process' apply()
  • Improve unit / integration test checks
  • libbmrm uninitialized memory reads
  • libocas uninitialized memory reads
  • Octave 3.8 compile fixes [Orion Poplawski]
  • Fix java modular compile error [Bjoern Esser]

Logo OptWok 0.3.1

by ong - May 2, 2013, 10:46:11 CET [ Project Homepage BibTeX Download ] 6652 views, 1283 downloads, 1 subscription

About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier.

Changes:
  • minor bugfix

Logo OpenGM 2 2.0.2 beta

by opengm - June 1, 2012, 14:33:53 CET [ Project Homepage BibTeX Download ] 2280 views, 504 downloads, 1 subscription

About: A C++ Library for Discrete Graphical Models

Changes:

Initial Announcement on mloss.org.


Logo Marray 2.2

by andres - July 6, 2011, 01:27:44 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2804 views, 664 downloads, 1 subscription

About: Fast Runtime-Flexible Multi-dimensional Arrays and Views for C++

Changes:

Initial Announcement on mloss.org.


Logo mldata.org svn-r1070-Apr-2011

by sonne - April 8, 2011, 10:15:49 CET [ Project Homepage BibTeX Download ] 3645 views, 669 downloads, 1 subscription

About: The source code of the mldata.org site - a community portal for machine learning data sets.

Changes:

Initial Announcement on mloss.org.


Logo mldata-utils 0.5.0

by sonne - April 8, 2011, 10:02:44 CET [ Project Homepage BibTeX Download ] 18529 views, 3871 downloads, 1 subscription

About: Tools to convert datasets from various formats to various formats, performance measures and API functions to communicate with mldata.org

Changes:
  • Change task file format, such that data splits can have a variable number items and put into up to 256 categories of training/validation/test/not used/...
  • Various bugfixes.

About: OpenGM is a free C++ template library, a command line tool and a set of MATLAB functions for optimization in higher order graphical models. Graphical models of any order and structure can be built either in C++ or in MATLAB, using simple and intuitive commands. These models can be stored in HDF5 files and subjected to state-of-the-art optimization algorithms via the OpenGM command line optimizer. All library functions can also be called directly from C++ code. OpenGM realizes the Inference Algorithm Interface (IAI), a concept that makes it easy for programmers to use their own algorithms and factor classes with OpenGM.

Changes:

Initial Announcement on mloss.org.