Heart Disease Prediction using Machine Learning Techniques

Authors: Prakash K.

Country: India

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Abstract: Predicting Heart Disease through Machine Learning Algorithms is the project. The primary objective of this with an estimated 17.9 million fatalities annually, or 31% of all deaths worldwide, cardiovascular diseases (CVDs) are the leading cause of death worldwide. Heart failure is a frequent occurrence brought on by CVDs, and this dataset includes 1015 instances 12 attributes that are predictive a possible heart disease. In this project, we compare various classifiers, such as KNN and logistic regression, and we suggest an ensemble classifier that can handle classifiers that are both powerful and weak since. It is able to handle a substantial quantity of training samples the data. This is able to provide predictive analysis and increased accuracy.

Keywords: KNN, Logistic Regression, Confusion Matrix, Correlation Matrix

Paper Id: 230512

Published On: 2024-03-21

Published In: Volume 12, Issue 2, March-April 2024

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