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Every year, this sickness affects many people, first in the USA and then in India. Heart disease, according to medical experts and academic studies is not an illness that appears out of nowhere rather, it develops over time as a result of an irregular lifestyle and a variety of physiological functions. when those symptoms start to show, people seek medical attention and undergo a variety of pricey tests and treatments. Therefore, prior to developing this sickness, people can gain knowledge about the patient condition from the findings of this research. This study gathered data from various sources and divided it into two groups, with 80% going to the training dataset and the remaining 20% going to the test dataset. It was attempted to improve accuracy using various classifier algorithms and then to summarize that accuracy. These methods include Nave Bayes, Logistic Regression, K-nearest Neighbor, Support Vector Machine, Random Forest Classifier, Decision Tree Classifier, and Support Vector Machine. SVM, Logistic Regression, and KNN provided accuracy comparable to or greater than other techniques. This essay makes a development about which factor, given a fundamental prefix such as sex, glucose, blood pressure, heart rate, etc., is vulnerable to heart disease. |
