Feature Extraction Using Naive Bayes and Logistic Regression for Survival of the COPD Patients

Constructive pulmonary disease related anomalies are the usual causes of loss of life around the globe. During morning time most heart patients are suffering from high blood pressure which is the major causes of death. Patients are in the resting stage and asymptotic until fatal event occurs. Selecting important features from the available data by applying the bayes technique for the COPD patients is an important classification technique that can help to predict heart diseases. The goal is to find the better accuracy to disclose the heart diseases using Naïve Bayes and logistic regression classification techniques.