A Machine Learning approach and probabilistic reasoning in the prog-nosis of risk factors for diabetes
Abstract
This research work proposes the design of a classification computational model through the use of Machine Learning techniques, we have chosen to work with machine learning supported by a probabilistic model that allows evaluating the risk factors of type 2 diabetes disease This model is based on the logistic regression method, which, according to the risk factors of the disease, will show as a result the percentage that the patient has of contracting it. The bibliographic research methodology was applied that provides the necessary knowledge to carry out this project in which tests were carried out to verify the behavior of each of the variables used in the probabilistic model, which will provide efficient results in a short time the period thus being a tool to support experts in decision-making and providing the appropriate diagnosis to prevent the disease.
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