Diagnóstico de Enfermedades Card´ıacas con los algoritmos supervisados Naives Bayesian
Abstract
Heart disease is the leading cause of the death in the present. This paper contrasts the performance between the different supervised algorithms of Machine Learning, applied in medicine field, with the Naive Bayes supervised algorithms to help classify patients prone to heart disease. As data source, 303 instances of patients with different characteristics were used and analized when the data was proccessed by the respective algorithms. The results with the Naives Bayes algorithm are promising, obtaining an accuracy of 86.81 % using the mentioned data source. This family of algorithm has a better performance compared to other Machine Learning algorithms such as Neural Networks, obtaining more precise results than those expected from humans doctors.
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References
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