Projects running under platform independent.
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Logo Partition Comparison 1.0

by andres - April 21, 2012, 03:26:47 CET [ Project Homepage BibTeX Download ] 1737 views, 432 downloads, 1 subscription

About: Fast C++ implementation of the variation of information (Meila 2003) and Rand index (Rand 1971) with MATLAB mex files

Changes:

Initial Announcement on mloss.org.


Logo MLFlex 02-21-2012-00-12

by srp33 - April 3, 2012, 16:44:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1898 views, 383 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 http://jmlr.csail.mit.edu/papers/volume13/piccolo12a/piccolo12a.pdf.)

Changes:

Initial Announcement on mloss.org.


About: This local and parallel computation toolbox is the Octave and Matlab implementation of several localized Gaussian process regression methods: the domain decomposition method (Park et al., 2011, DDM), partial independent conditional (Snelson and Ghahramani, 2007, PIC), localized probabilistic regression (Urtasun and Darrell, 2008, LPR), and bagging for Gaussian process regression (Chen and Ren, 2009, BGP). Most of the localized regression methods can be applied for general machine learning problems although DDM is only applicable for spatial datasets. In addition, the GPLP provides two parallel computation versions of the domain decomposition method. The easiness of being parallelized is one of the advantages of the localized regression, and the two parallel implementations will provide a good guidance about how to materialize this advantage as software.

Changes:

Initial Announcement on mloss.org.


Logo Sparse MultiTask Learning Toolbox 1.2

by rflamary - March 18, 2012, 11:31:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2885 views, 704 downloads, 1 subscription

About: This package is a set of Matlab scripts that implements the algorithms described in the submitted paper: "Lp-Lq Sparse Linear and Sparse Multiple Kernel MultiTask Learning".

Changes:

Initial Announcement on mloss.org.


Logo Nen Beta

by pascal - February 19, 2012, 00:31:34 CET [ Project Homepage BibTeX Download ] 2965 views, 891 downloads, 1 subscription

About: 3-layer neural network for regression with sigmoid activation function and command line interface similar to LibSVM.

Changes:

Initial Announcement on mloss.org.


Logo Large margin filtering 0.9

by rflamary - February 18, 2012, 15:50:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2498 views, 539 downloads, 1 subscription

About: Matlab SVM toolbox for learning large margin filters in signal or images.

Changes:

Initial Announcement on mloss.org.


Logo JMLR SSA Toolbox 1.3

by paulbuenau - January 24, 2012, 15:51:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11795 views, 3605 downloads, 1 subscription

About: The SSA Toolbox is an efficient, platform-independent, standalone implementation of the Stationary Subspace Analysis algorithm with a friendly graphical user interface and a bridge to Matlab. Stationary Subspace Analysis (SSA) is a general purpose algorithm for the explorative analysis of non-stationary data, i.e. data whose statistical properties change over time. SSA helps to detect, investigate and visualize temporal changes in complex high-dimensional data sets.

Changes:
  • Various bugfixes.

Logo pGBRT, Parallel Gradient Boosted Regression Trees 0.9

by swtyree - September 16, 2011, 22:15:46 CET [ Project Homepage BibTeX Download ] 6559 views, 1021 downloads, 1 subscription

About: Learns gradient boosted regression tree ensembles in parallel on shared memory or cluster systems

Changes:

Initial Announcement on mloss.org.


Logo MLPlot Beta

by pascal - August 22, 2011, 11:07:53 CET [ Project Homepage BibTeX Download ] 2196 views, 442 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


About: Multi-class vector classification based on cost function-driven learning vector quantization , minimizing misclassification.

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 ] 2869 views, 688 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


Logo Correlative Matrix Mapping, CMM 1.1

by emstrick - July 5, 2011, 15:15:21 CET [ BibTeX BibTeX for corresponding Paper Download ] 4336 views, 980 downloads, 1 subscription

About: Correlative Matrix Mapping (CMM) provides a supervised linear data mapping into a Euclidean subspace of given dimension. Applications include denoising, visualization, label-specific data preprocessing, and assessment of data attribute pairs relevant for the supervised mapping. Solving auto-association problems yields linear multidimensional scaling, similar to PCA, but usually with more faithful low-dimensional mappings.

Changes:

Tue Jul 5 14:40:03 CEST 2011 - Bugfixes and cleanups

  • single precision data affected pinv(). Now fairer using double precision.
  • early stopping did not work properly; now fixed
  • Hessian update mode globally controlled via hessmode, 'lbfgs' / 'bfgs'
  • distmat.m corrected for rounding problems and extended to distmat(X,Y)
  • replaced files: corv.m + corvgrad.m -> corvg.m
  • removed unused files: corrmat.m, splitdata.m, traforankapply.m

Logo Gird Soccer Simulator 1.0

by sina_iravanian - April 27, 2011, 16:47:38 CET [ Project Homepage BibTeX Download ] 2666 views, 758 downloads, 1 subscription

About: Grid-Soccer Simulator is a multi-agent soccer simulator in a grid-world environment. The environment provides a test-bed for machine-learning, and control algorithms, especially multi-agent reinforcement learning.

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 ] 3715 views, 689 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 Gibbs RTSS 1.0

by marc - April 4, 2011, 19:58:43 CET [ BibTeX BibTeX for corresponding Paper Download ] 2509 views, 655 downloads, 1 subscription

About: The software provides an implementation of a filter/smoother based on Gibbs sampling, which can be used for inference in dynamical systems.

Changes:

Initial Announcement on mloss.org.


Logo reserbot alpha 1

by neuromancer - January 31, 2011, 14:27:18 CET [ Project Homepage BibTeX Download ] 4180 views, 1138 downloads, 1 subscription

About: A chatterbot that learns natural languages learning from imitation.

Changes:

Alpha 1 - Codename: Wendell Borton ("Bllluuhhhhh...!!")

Short term memory greatly improved.


Logo KReator 1.2.3198

by mthimm - December 23, 2010, 12:07:25 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7743 views, 1613 downloads, 1 subscription

About: KReator is an integrated development environment (IDE) for relational probabilistic knowledge representation languages. At the moment, KReator supports Bayesian Logic Programs (BLPs), Markov Logic Networks (MLNs), Relational Maximum Entropy (RME), Relational Bayesian Networks (RBN), and Probabilistic Prolog (ProbLog).

Changes:
  • several bugfixes
  • Beta version of ProbLog plugin
  • enhanced command completion in console
  • enhanced error messages for syntax errors
  • refactored logic libraries
  • added prettyprint function in console
  • added syntax highlighting for RBNs

Logo Epistatic MAP Imputation 1.1

by colm - November 25, 2010, 21:01:10 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2654 views, 636 downloads, 1 subscription

About: Epistatic miniarray profiles (E-MAPs) are a high-throughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from E-MAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values - up to 35% - that can reduce the effectiveness of some data analysis techniques and prevent the use of others. This project contains nearest neighbor based tools for the imputation and prediction of these missing values. The code is implemented in Python and uses a nearest neighbor based approach. Two variants are used - a simple weighted nearest neighbors, and a local least squares based regression.

Changes:

Initial Announcement on mloss.org.


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.


Logo Pyriel 1.5

by tfawcett - October 27, 2010, 09:12:53 CET [ BibTeX BibTeX for corresponding Paper Download ] 10779 views, 2323 downloads, 1 subscription

About: Pyriel is a Python system for learning classification rules from data. Unlike other rule learning systems, it is designed to learn rule lists that maximize the area under the ROC curve (AUC) instead of accuracy. Pyriel is mostly an experimental research tool, but it's robust and fast enough to be used for lightweight industrial data mining.

Changes:

1.5 Changed CF (confidence factor) to do LaPlace smoothing of estimates. New flag "--score-for-class C" causes scores to be computed relative to a given (positive) class. For two-class problems. Fixed bug in example sampling code (--sample n) Fixed bug keeping old-style example formats (terminated by dot) from working. More code restructuring.


Showing Items 41-60 of 75 on page 3 of 4: Previous 1 2 3 4 Next