Search Results for "java machine learning library"
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Showing 9 open source projects for "java machine learning library"
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Uranie
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... -
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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
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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.
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Adaptive Gaussian Filtering
Machine learning with Gaussian kernels.
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. -
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A C++ library for machine learning within dynamic systems. It provides methods such as the Kalman, unscented Kalman, and particle filters and smoothers, as well as useful classes such as common probability distributions and stochastic processes.
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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.
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FLPD is an automatic learning system based on fuzzy prototypes, composed of a C++ library for machine learning and fuzzy logic and an experimentation framework.
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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.
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Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.
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