For strictly numeric data, one of the most common techniques for data clustering is called the k-means algorithm. The effectiveness and ... raw WCSS values into percentages of variability explained ...

Abstract: This paper presents a K-means clustering optimized fuzzy logic control algorithm (KC-FLC) for the detection of various arrhythmia in an ECG signal. For the arrhythmia classification, various ...

Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...

Clustering is an unsupervised machine learning technique that groups data points based on their similarities. K-Means Clustering, a popular clustering algorithm ... In the article, we explain how to ...