Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/77167
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dc.creatorFrancisco Reinaldo
dc.creatorMarcus Siqueira
dc.creatorRui Camacho
dc.creatorLuís Paulo Reis
dc.date.accessioned2022-09-11T13:26:19Z-
dc.date.available2022-09-11T13:26:19Z-
dc.date.issued2006
dc.identifier.issn1109-2777
dc.identifier.othersigarra:59269
dc.identifier.urihttps://hdl.handle.net/10216/77167-
dc.description.abstractThis paper presents the AFRANCI tool for the development of Multi-Strategy learning systems. Designing a Multi-Strategy system using AFRANCI is a two step process. The use interactively designs the structure of the system and then chooses the learning strategies for each module. After providing the datasets all modules as automatically trained. The system is aware and takes into consideration the inter-dependency of the modules. The tool has built-in learning algorithms but can use external programs implementing the learning algorithms. The tool has the following facilities. It allows any user to design in an interactive and easy fashion the structure of the target system. The structure of the target system is a collection of interconnected modules. The user may then choose the different learning algorithms to construct each module. The tool has several built-in Machine Learning algorithms has has interfaces that enables it to use external learning tools like WEKA and CN2. AFRANCI uses the interdependency of the modules to determine the sequence of training. For each module the system uses a wrapper to tune automatically the parameters of the learning algorithm. In the final step of the design sequence AFRANCI generates a compact and legible ready-to-use ANSI C open-source code for the final system.
dc.language.isoeng
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.titleMulti-strategy learning made easy
dc.typeArtigo em Revista Científica Internacional
dc.contributor.uportoFaculdade de Engenharia
dc.identifier.authenticusP-007-G0H
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

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