RSS 16 projects tagged "machine learning"

Download Website Updated 17 Feb 2014 SHOGUN

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Pop 359.42
Vit 38.88

SHOGUN is a machine learning toolbox whose focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It provides a generic SVM object interfacing to several different SVM implementations, all making use of the same underlying, efficient kernel implementations. Apart from SVMs and regression, SHOGUN also features a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons, and algorithms to train hidden Markov models. SHOGUN can be used from within C++, Matlab, R, Octave, and Python.

Download Website Updated 07 Apr 2014 Armadillo C++ Library

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Pop 612.44
Vit 136.73

Armadillo is a C++ linear algebra library (matrix maths) aiming towards a good balance between speed and ease of use. The API is deliberately similar to Matlab's. Integer, floating point, and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS numerics libraries. A delayed evaluation approach, based on template meta-programming, is used (during compile time) to combine several operations into one and reduce or eliminate the need for temporaries.

Download Website Updated 07 Nov 2013 Thinknowlogy

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Pop 217.84
Vit 12.73

Thinknowlogy is grammar-based software, designed to utilize the Natural Laws of Intelligence in grammar, in order to create intelligence through natural language in software. This is demonstrated by programming in natural language, reasoning in natural language and drawing conclusions (more detailed than scientific solutions), making assumptions (with self-adjusting level of uncertainty), asking questions (about gaps in the knowledge), and detecting conflicts in the knowledge. It builds semantics autonomously (with no vocabularies or words lists), detecting some cases of semantic ambiguity. It is multi-grammar, proving that Natural Laws of Intelligence are universal.

Download No website Updated 01 Oct 2010 Pinta

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Pop 60.91
Vit 2.53

Pinta is an extremely versatile, extensible, self-learning image classification program. It uses texture and color analysis and neural network techniques to automatically learn differences in images. It comes with a C API for easy integration into other software. It is built on top of the pattern recognition and image analysis platform Into.

Download No website Updated 13 Aug 2010 TexLexAn

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Pop 37.04
Vit 1.08

TexLexAn allows you to drag and drop a document or a link to any Web page to analyze. The program will analyze the text, evaluate its readability, categorize the document, summarize it, and archive it.

Download No website Updated 28 Jan 2010 Waffles

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Pop 26.83
Vit 39.22

Waffles is a cross-platform C++ library of algorithms for machine learning, artificial intelligence, data mining, etc. It also contains demo apps and command-line wrapper tools that are useful for visualizing, analyzing, and predictively modeling data.

No download Website Updated 06 May 2010 scikits.learn

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Pop 17.20
Vit 37.96

scikits.learn is a Python module that integrates classic machine learning algorithms in the tightly-knit world of scientific Python packages. It aims to provide simple and efficient solutions to learning problems that are accessible to everybody and reusable in various contexts: machine-learning as a versatile tool for science and engineering.

Download Website Updated 19 Jun 2013 Milk

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Pop 139.60
Vit 9.49

Milk is a machine learning toolkit in Python. Its focus is on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, and decision trees. It also performs feature selection. These classifiers can be combined in many ways to form different classification systems. For unsupervised learning, milk supports k-means clustering and affinity propagation.

Download Website Updated 06 Nov 2012 Accord.NET Framework

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Pop 74.30
Vit 3.48

Accord.NET provides statistical analysis, machine learning, image processing, and computer vision methods for .NET applications. The Accord.NET Framework extends the popular AForge.NET with new features, adding to a more complete environment for scientific computing in .NET.

No download Website Updated 15 Oct 2012 Fuzzy machine learning framework

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Pop 52.19
Vit 2.62

Fuzzy machine learning framework is a library and a GUI front-end for machine learning using intuitionistic fuzzy data. The approach is based on the intuitionistic fuzzy sets and the possibility theory. Further characteristics are fuzzy features and classes; numeric, enumeration features and features based on linguistic variables; user-defined features; derived and evaluated features; classifiers as features for building hierarchical systems; automatic refinement in case of dependent features; incremental learning; fuzzy control language support; object-oriented software design with extensible objects and automatic garbage collection; generic data base support through ODBC; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use.

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