A Fuzzy Poisson Naive Bayes classifier for epidemiological purposes

Statistical methods have been used to classify data in different areas. In epidemiological studies, some measures follow specific statistical distribution and compatible classifiers can be designed for those cases. Classifiers based on measures that follow Poisson distributions can be found in the scientific literature. Due to uncertainty on epidemiological measures, a fuzzy approach may be interesting and the present work proposes a new classifier named Fuzzy Poisson Naive Bayes (FPNB). The theoretical development is presented as well as results of its application on simulated multidimensional data. A brief comparison with a classical Poisson Naive Bayes classifier and with a Naive Bayes classifier is performed too.