Heart Disease Prediction with Machine Learning Approaches
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064


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Research Paper | Computer Science & Engineering | India | Volume 9 Issue 7, July 2020

Heart Disease Prediction with Machine Learning Approaches

Megha Kamboj

Heart is the most essential or crucial portion of our body. Heart is used to maintain and conjugate blood in our body. There are a lot of cases in the world related to heart diseases. People are leading to death due to heart disease. Various symptoms like chest pain, fasting of heartbeat and so on are mentioned. The health care industries found a large amount of data. This paper gives the idea of predicting heart disease using machine learning algorithms. Here, we will use various machine learning algorithms such as support vector classifier, random forest, knn, naïve bayes, decision tree and logistic regression. The algorithms are used on the basis of features and for predicting the heart disease. This paper uses different machine learning algorithms for comparing the accuracy among them.

Keywords: Coronary artery disease, Decision tree, K nearest neighbor, Machine Learning, Support vector, Accuracy, Logistic Regression, Naïve Bayes

Edition: Volume 9 Issue 7, July 2020

Pages: 1454 - 1458

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How to Cite this Article?

Megha Kamboj, "Heart Disease Prediction with Machine Learning Approaches", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SR20724113128, Volume 9 Issue 7, July 2020, 1454 - 1458

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