Clustering Arrhythmia Multiclass Using Fuzzy Robust Kernel C-Means (FRKCM)

Abstract

Irregularities in the rhythm of the heartbeat is known for arrhythmias. Which sometimes may occur sporadically in daily life. In this paper, Arrhythmia clustering proposed using Fuzzy robust kernel c-means to multiclass data Arrhythmia from the UCI machine learning repository. Kernel functions that will be used for this paper is RBF kernel and Polynomial kernel. A clustering algorithm can organize a set groups data objects into various clusters so that the data within the same cluster have high similarity in comparison to one another. Based on the experiments, it provides high clustering accuracy and effective diagnostic capabilities.