Electrocardiogram (ECG) data is quite useful to identify heart disease. In this work, MITBIH dataset is taken for this study. Machine learning classification of heart disease is done using Decision Tree and Random forest algorithm.

Random forest accuracy is higher than decision tree. Heart disease prediction is done with highest accuracy around 97% using MITBIH dataset. There are 5 different classes are labelled in the dataset.

Heart disease prediction is also done with Cleveland dataset for this check link

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