Caracterização da Mortalidade Infantil dos Estados de Santa Catarina e Amapá Utilizando Mineração de Dados - Soares, Wanderson L. G.; Lima, Patrícia; Zárate, Luis E.; Song, Mark A. Junho; Nobre, Cristiane N. (Anais do Symposium on Knowledge Discovery, Mining and Learning (KDMiLe); 2018: Anais do VI Symposium on Knowledge Discovery, Mining and LearningDO - 10.5753/kdmile.2018.27394, 2018)
The objective of this article is to use the concepts of knowledge discovery in databases, specifically the concepts of machine learning in the data mining phase, to characterize infant mortality in the state of Santa Catarina (with lower infant mortality rate) and in the state of Amapá (with the highest infant mortality rate). In this way, the classifiers J48, JRip and Random Forest were used and a brief comparison was made between the results obtained by the classifiers in both states. In addition, the database was preprocessed, which includes attribute selection and balancing, the application of data mining techniques and the analysis of the results of the respective models.