Search Results for "java machine learning library" - Page 6
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Showing 153 open source projects for "java machine learning library"
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Structlab is a machine learning C++ framework for structured domains, which provides a toolbox of learning methods and tools for preprocessing and visualization. It also provides a GUI to setup elaborate experiments in a visual and intuitive way.
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T-Rex (Trainable Relation Extraction) is a highly configurable machine learning-based Information Extraction from Text framework, which includes tools for document classification, entity extraction and relation extraction.
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TimeSleuth - Temporal Rule Discovery
Temporal and Causal Decision Rules
TimeSleuth discovers temporal decision rules. It also judges the (a)causality of the rules. TimeSleuth can discover rules that involve time: {if (rainy_yesterday = true) then rainy_today = true}, or {if (rainy_tomorrow = true) then rainy_today = true}. -
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DLESE (Digital Library for Earth System Education) is a community-supported digital library dedicated to the collection, enhancement, and distribution of materials that facilitate learning about the Earth. Sponsored by the US National Science Foundation.
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The Free Connectionist Q-learning Java Framework is an library for developing learning systems. Keywords: qlearning, artificial intelligence, alife, neural nets, neural networks, machine learning, reinforcement learning unsupervised learning agents lejos
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PepArML: An unsupervised, model-free, combining peptide identification arbiter for tandem mass spectra via machine learning.
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A Java-written MIPS simulator developed to stimulate people learning the Assembly language. It adds graphics, sounds and user interation to make writing assembly programs more interesting.
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BITXml is an open xml based protocol for Machine to Machine communications. BITXml is both language and "transport" agnostic and covers all the requirements of a generic M2M telemetry & control application. For more info www.bitxml.org
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The aim of the BioWeka project is to add bioinformatics functionalities such as e.g. alignments to the popular machine learning framework Weka.
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Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.
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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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The Pattern Analysis Library (PALib) is a C++ class library for pattern classification/recognition. PALib consists of a wide range of machine learning routines such as Bayesian decision theory, artificial neural networks, and fuzzy inference systems.
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The Wolfram Machine project is an effort to create a set of documentation and useful modules (both hardware and software) for a computing architecture based on the mathematical theories presented in Steven Wolfram's book _A_New_Kind_of_Science_.
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The OS561 operating system based around FORTH/Java. The OS is to run on a VHDL chip OpenHardware design called the Minon, but could become available for other platforms. The unique point of the design is a revolutionary data compression technology.
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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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JUDGE (Java Utility for Document Genre Eduction) features automatic classification and clustering of documents, optionally as a webservice. The program is written entirely in Java and makes use of the Weka machine learning toolkit.
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JavaHMI is a Java API for developing human machine interfaces. It is based on a observable/event driven control pattern. JavaHMI\'s graphical components can be programatically attached to embedded or remote machine control resources.
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Ruby SVM is a Ruby binding to the very popular and highly useful libsvm library (released under a seperate license) This allows you to effortlessly experiment with machine learning, in particular Support Vector Machines, in Ruby. SVM's have found use in
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HORUS is a system for knowledge acquisition, hypothesis generation, inference and learning. It is an interactive, internet environment accessible to a diverse community of users (public-access or membership basis) - see also UMKAILASH project for more.
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Weka-Parallel is a modification to Weka, created with the intention of being able to harness the power of Weka and the speed of parallel processing to be able to run a number of data mining and machine learning algorithms quickly.
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ITAS puts a human user in the place of a Robocup agent by providing a visual display of the agent's environment and an interface for controlling the agent. It also generates a log of the user's environment and actions for use in machine learning.
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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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The ROSETTA C++ library is a collection of C++ classes and routines that enable discernibility-based empirical modelling and data mining. Comprises useful routines for machine learning in general and for rough set theory in particular.
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AraRooter
Find Arabic Root Word
Using Machine Learning, AraRooter finds the three-lettered root of any Arabic lemma with around 84% accuracy. -
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Cinefile
A category-based approach to exploring film data.
Cinefile is a prototype of a category-based method of database exploration. It allows the user to identify abstract categories of films by providing examples of category members, learns to classify films as belonging or not belonging to those categories, and provides a graphical interface for exploring and comparing categories. Cinefile is designed to work with data retrieved from the Internet Movie Database (imdb.com). This data is used for classification and is the subject of the...
