Predict the Heart Disease Using a Logistic Regression Classifier Algorithm

Abstract

Machine learning (ML), a field of computer science, enables computer systems to interpret data similarly to how people do. Machine learning (ML) is an artificial intelligence technique that use an algorithm or technique to identify patterns in unstructured data. Making it possible for computers to learn from experience without explicit programming or human supervision is the main objective of machine learning (ML). Using well-labeled training data that has been used to train the machines, supervised learning is a type of machine learning in which the output is predicted by the computers. The phrase “labelled data” describes input data that has already been given the proper output. One of the most common diseases affecting people today is cardiovascular disease, which can result in a variety of medical problems. Significant morbidity, mortality, and monetary loss are all results of it. If this disease were promptly recognized and predicted, patients might have the opportunity to employ the appropriate prophylactic and treatment measures. To better understand risk factors, we predict heart diseases using a supervised learning method as a logistic regression model.