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| Registros recuperados: 90 | |
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| Destercke, S.; Guillaume, S.; Charnomordic, B.. |
| In many fields where human understanding plays a crucial role, such as bioprocesses, the capacity of extracting knowledge fromdata is of critical importance. Within this framework, fuzzy learning methods, if properly used, can greatly help human experts.Amongst these methods, the aim of orthogonal transformations, which have been proven to be mathematically robust, is to buildrules from a set of training data and to select the most important ones by linear regression or rank revealing techniques. The OLSalgorithm is a good representative of those methods. However, it was originally designed so that it only cared about numericalperformance. Thus, we propose some modifications of the original method to take interpretability into account. After recallingthe... |
| Tipo: Journal Article |
Palavras-chave: LOGIQUE FLOUE; INTERPRETATION; DETECTION D'INCIDENTS; ALGORYTHME; TRANSFORMATION ORTHOGONALE LEARNING; RULE INDUCTION; FUZZY LOGIC; INTERPRETABILITY; OLS; ORTHOGONAL TRANSFORMATIONS; DEPOLLUTION; FAULT DETECTION. |
| Ano: 2007 |
URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD200822fe4943&uri=/notices/prodinra1/2008/08/ |
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| Registros recuperados: 90 | |
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