Multiclass classification of cardiac arrhythmia from the ECG recordings
The goal of the work was to implement a machine learning model to classify patients in one of the four classes of cardiac arrhythmias, so the ultimate goal would be to help the diagnosis by the doctor and decide if the category of patients is normal, ventricular arrhythmia, atrial arrhythmia or ischemia. The pipeline followed included a phase of data preprocessing, partition of the dataset, feature selection, cross validation and final test with the best model.