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Feature construction and selection are two key factors in the field of Machine Learning (ML). Usually, these are very time-consuming and complex tasks because the features have to be manually crafted. The features are aggregated, combined or split to create features from raw data. This project makes use of ontologies to automatically generate features for the ML algorithms.
A set of powerful tools to perform TDD on MAS based on JADE
The TDD MAS Toolkit provides a set of tools to perform Test Driven Development of MAS based on Jade. The toolkit allows developers to set up simulation based and test case scenario based testing, providing powerful insights of the MAS under construction and assuring that the interation protocols and agent interaction in general are been enacted as expected.
Dataset Retrieval through Intelligent Agents (DARIA): is an Open Source project for facilitating the construction of ARFF data set files for use with WEKA or any such Machine Learning/Data Mining Software through the use of Intelligent Agents.
Vademecum is a Data Mining suite with a novel help function, semi-automated protocol, consequently modular construction that is also equipped with the most elaborated Data Mining methods.
New customers can spin up VMs, build with AI, and query data at no cost.
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OntoCardio is an initiative to build ontologies for the legacy Cardio Database (Resource of bioinformation on cardiovascular diseases). SMI's Protege and its OWL plug-in has been adopted as the ontology construction and programming framework.
A group of systems for building network-oriented intelligent agents, consisting an agent communications infrastructure, April - an agent construction programming language, Go! - a logic programming language and DialoX - an XML-based user interface engine