Projects supporting the csv data format.
Showing Items 1-20 of 41 on page 1 of 3: 1 2 3 Next

Logo Distributed Frank Wolfe Algorithm 0.02

by alirezabagheri - January 28, 2015, 00:35:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 242 views, 35 downloads, 2 subscriptions

About: Distributed optimization: Support Vector Machines and LASSO regression on distributed data

Changes:

Initial Upload


Logo Hub Miner 1.1

by nenadtomasev - January 22, 2015, 16:33:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 874 views, 136 downloads, 1 subscription

About: Hubness-aware Machine Learning for High-dimensional Data

Changes:
  • BibTex support for all algorithm implementations, making all of them easy to reference (via algref package).

  • Two more hubness-aware approaches (meta-metric-learning and feature construction)

  • An implementation of Hit-Miss networks for analysis.

  • Several minor bug fixes.

  • The following instance selection methods were added: HMScore, Carving, Iterative Case Filtering, ENRBF.

  • The following clustering quality indexes were added: Folkes-Mallows, Calinski-Harabasz, PBM, G+, Tau, Point-Biserial, Hubert's statistic, McClain-Rao, C-root-k.

  • Some more experimental scripts have been included.

  • Extensions in the estimation of hubness risk.

  • Alias and weighted reservoir methods for weight-proportional random selection.


Logo ExtRESCAL 0.7.2

by nzhiltsov - January 20, 2015, 00:35:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3730 views, 676 downloads, 2 subscriptions

About: Scalable tensor factorization

Changes:
  • Improve (speed up) initialization of A by summation

Logo JMLR MLPACK 1.0.12

by rcurtin - January 7, 2015, 19:23:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 37923 views, 7374 downloads, 6 subscriptions

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

Changes:
  • Switch to 3-clause BSD license.

Logo python weka wrapper 0.2.2

by fracpete - January 5, 2015, 03:43:56 CET [ Project Homepage BibTeX Download ] 8565 views, 1807 downloads, 3 subscriptions

About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

Changes:
  • added convenience methods "no_class" (to unset class) and "has_class" (class set?) to "Instances" class
  • switched to using faster method objects for methods "classify_instance"/"distribution_for_instance" in "Classifier" class
  • switched to using faster method objects for methods "cluster_instance"/"distribution_for_instance" in "Clusterer" class
  • switched to using faster method objects for methods "class_index", "is_missing", "get/set_value", "get/set_string_value", "weight" in "Instance" class
  • switched to using faster method objects for methods "input", "output", "outputformat" in "Filter" class
  • switched to using faster method objects for methods "attribute", "attribute_by_name", "num_attributes", "num_instances", "class_index", "class_attribute", "set_instance", "get_instance", "add_instance" in "Instances" class

Logo Armadillo library 4.600

by cu24gjf - January 5, 2015, 01:22:25 CET [ Project Homepage BibTeX Download ] 49951 views, 10690 downloads, 4 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:
  • added .head() and .tail() to submatrix views
  • faster matrix transposes within compound expressions
  • faster accu() and norm() when compiling with -O3 -ffast-math -march=native (gcc and clang)
  • improved documentation

Logo ADAMS 0.4.7

by fracpete - December 24, 2014, 02:57:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8864 views, 2033 downloads, 2 subscriptions

About: The Advanced Data mining And Machine learning System (ADAMS) is a novel, flexible workflow engine aimed at quickly building and maintaining real-world, complex knowledge workflows.

Changes:
  • 51 new actors
  • 16 new conversions
  • new module adams-jooq: code generation from JDBC databases for typed access
  • new module adams-image-webservice: allows upload of images using webservice
  • adams-timeseries module extended
  • adams-spreadsheet module extended
  • adams-random module extended
  • adams-imaging module overhaul

Logo JMLR dlib ml 18.12

by davis685 - December 20, 2014, 22:38:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 90456 views, 15750 downloads, 2 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 tools for computing 2D FFTs, Hough transforms, image skeletonizations, and also a simple and type safe API for calling C++ code from MATLAB.


Logo JMLR JKernelMachines 2.5

by dpicard - December 11, 2014, 17:51:42 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15083 views, 3625 downloads, 4 subscriptions

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About: machine learning library in java for easy development of new kernels

Changes:

Version 2.5

  • New active learning algorithms
  • Better threading management
  • New multiclass SVM algorithm based on SDCA
  • Handle class balancing in cross-validation
  • Optional support of EJML switch to version 0.26
  • Various bugfixes and improvements

Logo The Statistical ToolKit 0.8.4

by joblion - December 5, 2014, 13:21:47 CET [ Project Homepage BibTeX Download ] 841 views, 326 downloads, 2 subscriptions

About: STK++: A Statistical Toolkit Framework in C++

Changes:

Inegrating openmp to the current release. Many enhancement in the clustering project. bug fix


Logo BayesPy 0.2.3

by jluttine - December 3, 2014, 14:51:10 CET [ Project Homepage BibTeX Download ] 3049 views, 820 downloads, 3 subscriptions

About: Variational Bayesian inference tools for Python

Changes:
  • Fix matplotlib compatibility broken by recent changes in matplotlib>=1.4.0
  • Add random sampling for Binomial and Bernoulli nodes
  • Fix minor bugs, for instance, in plot module

Logo LogRegCrowds, Logistic Regression from Crowds 1.0

by fmpr - October 30, 2014, 19:10:23 CET [ Project Homepage BibTeX Download ] 499 views, 126 downloads, 2 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.


Logo pySPACE 1.2

by krell84 - October 29, 2014, 15:36:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2539 views, 535 downloads, 1 subscription

About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.

Changes:

improved testing, improved documentation, windows compatibility, more algorithms


Logo BACOM2 1.0

by fydennis - October 24, 2014, 15:25:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 613 views, 118 downloads, 2 subscriptions

About: revised version of BACOM

Changes:

Initial Announcement on mloss.org.


Logo JMLR Waffles 2014-07-05

by mgashler - July 20, 2014, 04:53:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 25993 views, 7581 downloads, 2 subscriptions

About: Script-friendly command-line tools for machine learning and data mining tasks. (The command-line tools wrap functionality from a public domain C++ class library.)

Changes:

Added support for CUDA GPU-parallelized neural network layers, and several other new features. Full list of changes at http://waffles.sourceforge.net/docs/changelog.html


Logo Encog Machine Learning Framework 3.2

by jeffheaton - July 5, 2014, 23:47:06 CET [ Project Homepage BibTeX Download ] 3357 views, 804 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 MultiBoost 1.2.02

by busarobi - March 31, 2014, 16:13:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 25629 views, 4463 downloads, 1 subscription

About: MultiBoost is a multi-purpose boosting package implemented in C++. It is based on the multi-class/multi-task AdaBoost.MH algorithm [Schapire-Singer, 1999]. Basic base learners (stumps, trees, products, Haar filters for image processing) can be easily complemented by new data representations and the corresponding base learners, without interfering with the main boosting engine.

Changes:

Major changes :

  • The “early stopping” feature can now based on any metric output with the --outputinfo command line argument.

  • Early stopping now works with --slowresume command line argument.

Minor fixes:

  • More informative output when testing.

  • Various compilation glitch with recent clang (OsX/Linux).


Logo JMLR EnsembleSVM 2.0

by claesenm - March 31, 2014, 08:06:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6226 views, 2234 downloads, 2 subscriptions

About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semi-supervised tasks.

Changes:

The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:

  1. Support for multithreading in training and prediction with ensemble models. Since both of these are embarassingly parallel, this has induced a significant speedup (3-fold on quad-core).
  2. Extensive programming framework for aggregation of base model predictions which allows highly efficient prototyping of new aggregation approaches. Additionally we provide several predefined strategies, including (weighted) majority voting, logistic regression and nonlinear SVMs of your choice -- be sure to check out the esvm-edit tool! The provided framework also allows you to efficiently program your own, novel aggregation schemes.
  3. Full code transition to C++11, the latest C++ standard, which enabled various performance improvements. The new release requires moderately recent compilers, such as gcc 4.7.2+ or clang 3.2+.
  4. Generic implementations of convenient facilities have been added, such as thread pools, deserialization factories and more.

The API and ABI have undergone significant changes, many of which are due to the transition to C++11.


Logo Chordalysis 1.0

by fpetitjean - March 24, 2014, 01:22:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1188 views, 303 downloads, 1 subscription

About: Log-linear analysis for high-dimensional data

Changes:

Initial Announcement on mloss.org.


Logo MOSIS 0.55

by claasahl - March 9, 2014, 17:35:40 CET [ BibTeX Download ] 3286 views, 1034 downloads, 2 subscriptions

About: MOSIS is a modularized framework for signal processing, stream analysis, machine learning and stream mining applications.

Changes:
  • Move "flow"-related classes into package "de.claas.mosis.flow" (e.g. Node and Link).
  • Refined and improved "flow"-related tests (e.g. Iterator and Node tests).
  • Refactored tests for data formats (e.g. PlainText and JSON tests).
  • Added visitor design pattern for graph-based functions (e.g. initialization and processing).
  • Documented parameters of Processor implementations.

Showing Items 1-20 of 41 on page 1 of 3: 1 2 3 Next