Classification of Cardiac Arrhythmia

Classification of Cardiac Arrhythmia

A python based tool developed to classify different types of cardiac arrhythmia given ECG readings.

Artificial Intelligence

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Description

A supervised machine learning classifier based on Voting Feature Intervals (VFI) algorithm is developed for the detection of the type of cardiac arrhythmia on a standard UCI dataset. Five different VFI techniques were implemented on the ECG data obtained from the UCI repository. A few popular algorithms such as Naïve Bayes, Decision Tree, Support Vector Machines (SVM) and k­Nearest Neighbour (kNN) were also implemented. The accuracy of each algorithm was validated using k­fold cross validation and plotted using MATLAB. The accuracies were compared to choose the best algorithm for this particular problem.

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Parag J. (Intel) created project Classification of Cardiac Arrhythmia

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Classification of Cardiac Arrhythmia

A supervised machine learning classifier based on Voting Feature Intervals (VFI) algorithm is developed for the detection of the type of cardiac arrhythmia on a standard UCI dataset. Five different VFI techniques were implemented on the ECG data obtained from the UCI repository. A few popular algorithms such as Naïve Bayes, Decision Tree, Support Vector Machines (SVM) and k­Nearest Neighbour (kNN) were also implemented. The accuracy of each algorithm was validated using k­fold cross validation and plotted using MATLAB. The accuracies were compared to choose the best algorithm for this particular problem.

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