Automatic Classification of NCM Codes Using the Naïve Bayes Algorithm - Batista, Rodrigo de Abreu; Bagatini, Daniela D. S.; Frozza, Rejane (iSys - Journal of Information Systems, 2018)
This paper consists of the development of a classifier for the automatic categorization of product item descriptions into their appropriate Common Mercosul Nomenclature (NCM) codes. This classifier was developed using the Naïve Bayes supervised learning algorithm. For training, data from items of consumer invoices belonging to chapters 22 and 90 of the NCM were used. The results evidenced the capacity of the model to correctly classify the instances. For the simpler and easier data set, based on chapter 22, an accuracy of 98% was obtained, while for the medium and difficult sets, based on chapters 22 and 90, the accuracy obtained was 90% and 83%, respectively.