Projects that are tagged with algorithms.
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Logo SALSA.jl 0.0.5

by jumutc - September 28, 2015, 17:28:56 CET [ Project Homepage BibTeX Download ] 212 views, 26 downloads, 1 subscription

About: SALSA (Software lab for Advanced machine Learning with Stochastic Algorithms) is an implementation of the well-known stochastic algorithms for Machine Learning developed in the high-level technical computing language Julia. The SALSA software package is designed to address challenges in sparse linear modelling, linear and non-linear Support Vector Machines applied to large data samples with user-centric and user-friendly emphasis.


Initial Announcement on

Logo ELKI 0.7.0-20150828

by erich - September 17, 2015, 10:20:30 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14599 views, 2678 downloads, 4 subscriptions

About: ELKI is a framework for implementing data-mining algorithms with support for index structures, that includes a wide variety of clustering and outlier detection methods.


Additions and Improvements from ELKI 0.6.0:

  • Uncertain data types, and clustering algorithms for uncertain data.

  • Major refactoring of distances - removal of Distance values and removed support for non-double-valued distance functions. While this reduces the generality of ELKI, we could remove about 2.5% of the codebase by not having to have optimized codepaths for double-distance anymore. Generics for distances were present in almost any distance-based algorithm, and we were also happy to reduce the use of generics this way. Support for non-double-valued distances can trivially be added again, e.g. by adding the specialization one level higher: at the query instead of the distance level, for example.

  • In this process, we also removed the Generics from NumberVector. The object-based get was deprecated for a good reason long ago, and e.g. doubleValue are more efficient (even for non-DoubleVectors).

  • Dropped some long-deprecated classes

Clustering algorithms:


  • speedups for some initialization heuristics
  • K-means++ initialization no longer squares distances (again)
  • farthest-point heuristics now uses minimum instead of sum (renamed)
  • additional evaluation criteria
  • Elkan's and Hamerly's faster k-means variants

CLARA clustering


Hierarchical clustering

  • Renamed naive algorithm to AGNES
  • Anderbergs algorithm (faster than AGNES, slower than SLINK)
  • CLINK for complete linkage clustering in O(n²) time, O(n) memory
  • Simple extraction from HDBSCAN
  • "Optimal" extraction from HDBSCAN
  • HDBSCAN, in two variants

LSDBC clustering

EM clustering was refactored and moved into its own package. The new version is much more extensible.

Parallel computation framework, and some parallelized algorithms

  • Parallel k-means
  • Parallel LOF and variants


  • LibSVM format parser


  • kNN classification (with index acceleration)

Evaluation: Internal cluster evaluation:

  • Silhouette index
  • Simplified Silhouette index (faster)
  • Davis-Bouldin index
  • PBM index
  • Variance-Ratio-Criteria
  • Sum of squared errors
  • C-Index
  • Concordant pair indexes (Gamma, Tau)
  • Different noise handling strategies for internal indexes

Statistical dependence measures:

  • Distance correlation dCor.
  • Hoeffings D.
  • Some divergence / mutual information measures.

Distance functions:

  • Big refactoring.
  • Time series distances refactored, allow variable length series now.
  • Hellinger distance and kernel function.


  • Faster MDS implementation using power iterations.

Indexing improvements:

  • Precomputed distance matrix "index".
  • iDistance index (static only).
  • Inverted-list index for sparse data and cosine/arccosine distance.
  • cover tree index (static only).

Frequent Itemset Mining:

  • Improved APRIORI implementation.
  • FP-Growth added.
  • Eclat (basic version only) added.

Uncertain clustering:

  • Discrete and continuous data models
  • FDBSCAN clustering
  • UKMeans clustering
  • CKMeans clustering
  • Representative Uncertain Clustering (Meta-algorithm)
  • Center-of-mass meta Clustering (allows using other clustering algorithms on uncertain objects) (KDD'14)

Outlier detection changes / smaller improvements:

  • KDEOS outlier detection (SDM14)
  • k-means based outlier detection (distance to centroid) and Silhouette coefficient based approach (which does not work too well on the toy data sets - the lowest silhouette are usually where two clusters touch).
  • bug fix in kNN weight, when distances are tied and kNN yields more than k results.
  • kNN and kNN weight outlier have their k parameter changed: old 2NN outlier is now 1NN outlier, as commonly understood in classification literature (1 nearest neighbor ''other than the query object''; whereas in database literature the 1NN is usually the query object itself). You can get the old result back by decreasing k by one easily.
  • LOCI implementation is now only O(n^3 log n) instead of O(n^4).


  • MiniGUI has two "secret" new options: -minigui.last -minigui.autorun to load the last saved configuration and run it, for convenience.

  • Logging API has been extended, to make logging more convenient in a number of places (saving some lines for progress logging and timing).

Logo JMLR dlib ml 18.17

by davis685 - August 16, 2015, 04:33:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 113386 views, 18986 downloads, 4 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.


This release adds new clustering tools as well as upgrades the shape_predictor to allow training on datasets with missing landmarks. It also includes bug fixes and minor usability improvements.

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 ] 11902 views, 2245 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.


Updated to version 0.3.0

Logo Cognitive Foundry 3.4.1

by Baz - May 13, 2015, 06:55:24 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21783 views, 3602 downloads, 3 subscriptions

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

  • General:
    • Updated MTJ to version 1.0.2 and netlib-java to 1.1.2.
    • Updated XStream to version 1.4.8.
  • Common:
    • Fixed issue in VectorUnionIterator.
  • Learning:
    • Added Alternating Least Squares (ALS) Factorization Machine training implementation.
    • Fixed performance issue in Factorization Machine where linear component was not making use of sparsity.
    • Added utility function to sigmoid unit.

Logo Accord.NET Framework 2.14.0

by cesarsouza - December 9, 2014, 23:04:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 22046 views, 4545 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.


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:

Logo MyMediaLite 3.10

by zenog - October 8, 2013, 22:29:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 55382 views, 10286 downloads, 1 subscription

About: MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms.


Mostly bug fixes.

For details see:

Logo Neural network designer 1.1.1

by bragi - December 28, 2012, 11:38:10 CET [ Project Homepage BibTeX Download ] 4641 views, 1117 downloads, 1 subscription

About: a dbms for resonating neural networks. Create and use different types of machine learning algorithms.


AIML compatible (AIML files can be imported); new 'Grid channel' for developing board games; improved topics editor; new demo project: ALice (from AIML); lots of bug-fixes and speed improvements

Logo MROGH 1.0

by openpr_nlpr - October 16, 2012, 04:41:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2695 views, 575 downloads, 1 subscription

About: An implementation of MROGH descriptor. For more information, please refer to: “Bin Fan, Fuchao Wu and Zhanyi Hu, Aggregating Gradient Distributions into Intensity Orders: A Novel Local Image Descriptor, CVPR 2011, pp.2377-2384.” The most up-to-date information can be found at :


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Logo Linear SVM with general regularization 1.0

by rflamary - October 5, 2012, 15:34:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3653 views, 1022 downloads, 1 subscription

About: This package is an implementation of a linear svm solver with a wide class of regularizations on the svm weight vector (l1, l2, mixed norm l1-lq, adaptive lasso). We provide solvers for the classical single task svm problem and for multi-task with joint feature selection or similarity promoting term.


Initial Announcement on

Logo MDP Modular toolkit for Data Processing 3.3

by otizonaizit - October 4, 2012, 15:17:33 CET [ Project Homepage BibTeX Download ] 19701 views, 4955 downloads, 1 subscription

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About: MDP is a Python library of widely used data processing algorithms that can be combined according to a pipeline analogy to build more complex data processing software. The base of available algorithms includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.


What's new in version 3.3?

  • support sklearn versions up to 0.12
  • cleanly support reload
  • fail gracefully if pp server does not start
  • several bug-fixes and improvements

Logo Large margin filtering 0.9

by rflamary - February 18, 2012, 15:50:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3495 views, 823 downloads, 1 subscription

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


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Logo BCILAB 1.0-beta

by chkothe - January 6, 2012, 23:47:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4527 views, 950 downloads, 1 subscription

About: MATLAB toolbox for advanced Brain-Computer Interface (BCI) research.


Initial Announcement on

Logo NetPro 1.1.17

by lml - January 25, 2011, 19:02:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4188 views, 1011 downloads, 1 subscription

About: Tools for functional network analysis.


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Logo yaplf 0.7

by malchiod - April 22, 2010, 11:34:07 CET [ Project Homepage BibTeX Download ] 4040 views, 1013 downloads, 1 subscription

About: yaplf (Yet Another Python Learning Framework) is an extensible machine learning framework written in python


Initial Announcement on

Logo JMLR Java Machine Learning Library 0.1.5

by thomas - August 20, 2009, 23:47:45 CET [ Project Homepage BibTeX Download ] 21178 views, 2967 downloads, 1 subscription

About: Java-ML is a collection of machine learning and data mining algorithms, which aims to be a readily usable and easily extensible API for both software developers and research scientists.


new release

Logo Piqle 2.0

by fdecomite - June 19, 2009, 10:16:53 CET [ Project Homepage BibTeX Download ] 3994 views, 1930 downloads, 1 subscription

About: Piqle (Platform for Implementing Q-Learning Experiments) is a Java framework for fast design, prototyping and test of reinforcement learning experiments (RL). By clearly separating algorithms and problems, it allows users to focus on either part of the RL paradigm:designing new algorithms or implementing new problems. Piqle implements many classical RL algorithms, making their parameters easily tunable. At this time, 13 problems are implemented, several with one or more variants. The user's manual explains in detail how to code a new problem. Written in Java, Piqle is as platform-independent as Java itself. Its components can easily be embedded as part of complex implementations, like robotics or decision making.


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Logo Aleph 0.6

by jiria - January 12, 2009, 20:52:12 CET [ Project Homepage BibTeX Download ] 8393 views, 2358 downloads, 1 subscription

About: Aleph is both a multi-platform machine learning framework aimed at simplicity and performance, and a library of selected state-of-the-art algorithms.


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Logo LaRank 1.1

by antojne - July 15, 2008, 15:58:25 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 7829 views, 1515 downloads, 1 subscription

About: LaRank is an online solver for multiclass Support Vector Machines.


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Logo Nested Effects Models 2.4.0

by florian - July 8, 2008, 00:05:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6132 views, 1568 downloads, 1 subscription

About: Nested Effects Models (NEMs) are a class of directed graphical models originally introduced to analyze the effects of gene perturbation screens with high-dimensional phenotypes. In contrast to other [...]


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Showing Items 1-20 of 21 on page 1 of 2: 1 2 Next