An approach to the classification and Knowledge Extraction via microarrays by using Formal Concepts Analysis
Résumé
The classification and extraction of knowledge resulting from microarrays are a growing field which gave rise to several research tasks, however these works have not been able yet to be freed with the problems dependant between relations of all genes implied in breast cancer's disease. Moreover, the suggested methods generated some limiting dependency on the format of the treated data and extraction knowledge method. In this article, we present a method of classification and extraction of knowledge to handle data resulting from the microarrays. This method makes it initially possible to classify genes or the patients who have similar profiles of expression, and then to interpret the groups obtained. It is about a coupling between an algorithm of classification and an algorithm of extraction's rules associations. This work was validated by an expert. The obtained results seem to be interesting and promising owing to the fact that extracted knowledge can be used in the clinical medium to discriminate a disease or the state of a patient
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