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Logo MIPS, The migrant implementation system 1.0

by thomasfannes - April 28, 2015, 15:07:05 CET [ Project Homepage BibTeX Download ] 1158 views, 351 downloads, 3 subscriptions

About: MIPS is a software library for state-of-the-art graph mining algorithms. The library is platform independent, written in C++(03), and aims at implementing generic and efficient graph mining algorithms.


description update

Logo MIToolbox 2.1

by apocock - June 30, 2014, 01:05:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 20392 views, 3703 downloads, 1 subscription

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.


Added weighted entropy functions. Fixed a few memory handling bugs.

Logo mldata-utils 0.5.0

by sonne - April 8, 2011, 10:02:44 CET [ Project Homepage BibTeX Download ] 25222 views, 5431 downloads, 1 subscription

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

  • 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.

Logo svn-r1070-Apr-2011

by sonne - April 8, 2011, 10:15:49 CET [ Project Homepage BibTeX Download ] 4656 views, 1030 downloads, 1 subscription

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


Initial Announcement on

Logo MLDemos 0.5.1

by basilio - March 2, 2013, 16:06:13 CET [ Project Homepage BibTeX Download ] 23737 views, 5440 downloads, 2 subscriptions

About: MLDemos is a user-friendly visualization interface for various machine learning algorithms for classification, regression, clustering, projection, dynamical systems, reward maximisation and reinforcement learning.


New Visualization and Dataset Features Added 3D visualization of samples and classification, regression and maximization results Added Visualization panel with individual plots, correlations, density, etc. Added Editing tools to drag/magnet data, change class, increase or decrease dimensions of the dataset Added categorical dimensions (indexed dimensions with non-numerical values) Added Dataset Editing panel to swap, delete and rename dimensions, classes or categorical values Several bug-fixes for display, import/export of data, classification performance

New Algorithms and methodologies Added Projections to pre-process data (which can then be classified/regressed/clustered), with LDA, PCA, KernelPCA, ICA, CCA Added Grid-Search panel for batch-testing ranges of values for up to two parameters at a time Added One-vs-All multi-class classification for non-multi-class algorithms Trained models can now be kept and tested on new data (training on one dataset, testing on another) Added a dataset generator panel for standard toy datasets (e.g. swissroll, checkerboard,...) Added a number of clustering, regression and classification algorithms (FLAME, DBSCAN, LOWESS, CCA, KMEANS++, GP Classification, Random Forests) Added Save/Load Model option for GMMs and SVMs Added Growing Hierarchical Self Organizing Maps (original code by Michael Dittenbach) Added Automatic Relevance Determination for SVM with RBF kernel (Thanks to Ashwini Shukla!)

Logo MLFlex 02-21-2012-00-12

by srp33 - April 3, 2012, 16:44:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2996 views, 625 downloads, 1 subscription

About: Motivated by a need to classify high-dimensional, heterogeneous data from the bioinformatics domain, we developed ML-Flex, a machine-learning toolbox that enables users to perform two-class and multi-class classification analyses in a systematic yet flexible manner. ML-Flex was written in Java but is capable of interfacing with third-party packages written in other programming languages. It can handle multiple input-data formats and supports a variety of customizations. MLFlex provides implementations of various validation strategies, which can be executed in parallel across multiple computing cores, processors, and nodes. Additionally, ML-Flex supports aggregating evidence across multiple algorithms and data sets via ensemble learning. (See


Initial Announcement on

Logo MLlib 0.8

by atalwalkar - October 10, 2013, 00:56:25 CET [ Project Homepage BibTeX Download ] 2949 views, 564 downloads, 1 subscription

About: MLlib provides a distributed machine learning (ML) library to address the growing need for scalable ML. MLlib is developed in Spark (, a cluster computing system designed for iterative computation. Moreover, it is a component of a larger system called MLbase ( that aims to provide user-friendly distributed ML functionality both for ML researchers and domain experts. MLlib currently consists of scalable implementations of algorithms for classification, regression, collaborative filtering and clustering.


Initial Announcement on

Logo svn-r645-Mar-2011

by sonne - March 23, 2011, 11:09:18 CET [ Project Homepage BibTeX Download ] 17356 views, 2512 downloads, 1 subscription

About: This is the source code of the website.


Now works with newer django versions and fixes several warnings and minor bugs underneath. The only user visible change is probably that the subscription and bookmark buttons work again.

Logo JMLR MLPACK 1.0.12

by rcurtin - January 7, 2015, 19:23:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 49260 views, 9290 downloads, 6 subscriptions

Rating Whole StarWhole StarWhole StarWhole Star1/2 Star
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About: A scalable, fast C++ machine learning library, with emphasis on usability.

  • Switch to 3-clause BSD license.

Logo MLPlot Beta

by pascal - August 22, 2011, 11:07:53 CET [ Project Homepage BibTeX Download ] 2942 views, 694 downloads, 1 subscription

About: MLPlot is a lightweight plotting library written in Java.


Initial Announcement on

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