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Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr).
It provides various tools for:
- data analysis
- sampling
- statistical modeling
- optimisation
- sensitivity analysis
- uncertainty analysis
- running code on high performance computers
- etc.
Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python.
Is is...
This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet.
The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people.
AFNER is a C++ named entity recognition system that uses machine learning techniques. It is customisable to various domains. It also allows for multiple and overlapping named entity labels.
A broad collection of command-line-interface tools for performing machine learning operations. Each tool is a thin wrapper around functionality in a well-documented C++ class library. Waffles tools are designed to be simple, script-friendly, and to
libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation...
Content Addressable Memory, Multi-Variate Statistics, Data Mining Includes analyzing datasets, extracting patterns, creating empirical expert system. Computes joint probabilities and implements a "belief" as the solution of an equilibrium equation
Bidirectional computer, bicomp, is a virtualmachine designed to aid in the research of complexity. bicomp runs its programs in forward or reverse. The program either produces a result from two inputs, or a list of possible inputs given a result.
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Zabal6 is a machine learning student tool based on decision tree learning, focused in the area of knowledge discovery (data mining), and inspired on See5. Zabl6 is a C++ program for Linux and windows O.S, with a intuitive graphical interface.
PCP (Pattern Classification Program) is an open-source machine learning program for supervised classification of patterns. PCP is a binary executable running on Linux and Windows (under Cygwin environment).
MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning. The code is well documented and easy to extend, especially for adding new weak learners.
This project make some utilities based on FSM(Finited State Machine). The primary goal is to develop some auto generators, output source code or executable binary file. Anyway, it provide a trusty and high-efficient implement of FSM.
The result is only a
Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.