A new supervised learning algorithm inspired on chemical organic compounds
Ponce Espinosa, Hiram Eredín.
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In this work, a new supervised learning method called artificial organic networks is proposed for modeling problems, i.e. fitting, analyzing, inference and classification. In fact, this technique is inspired on chemical organic compounds due to their characteristics of stability, encapsulation, inheritance, organization, and robustness. Additionally, this work presentsartificial hydrocarbon networks, a supervised learning algorithm inspired on chemical hydrocarbon compounds and proposed under artificial organic networks technique.