Evaluating Classification Algorithms performance with Matlab for generating alerts of risk of infant death
Abstract: GISSA is an intelligent system for health decision making focused on childish maternal care. In this system, are generated alerts that involve the five health domains: clinicalepidemiological, normative, administrative, knowledge management and shared knowledge. The system proposes to contribute to the reduction of child mortality in Brazil. Thus, this paper presents studies over an intelligent module that uses Machine Learning to generate child death risk alerts on GISSA. These studies focus on trying different classification Algorithms, with a methodology based on Data Mining to reach a learning model capable of calculating the probability of a newborn dying. The work brings together public databases SIM and SINASC for the training of classification algorithms, identifying relationships between birth and death data of children under one year. During the methodological process, it was made a subsampling to balance the number of inputs and be fair in the training model results, executed with Matlab scripts.