The analysis is performed in R, which is a free and open source programming language mainly used for statistical computing. This paper summarizes the experimental analysis conducted on the performance of multiple clustering algorithms based on cardinality and dimensionality. The motivation behind this work is the scarcity of literatures dealing with performance of clustering algorithms in terms of turnaround time. A bunch of literatures can be found focusing on the quality of clustering algorithms using various internal and external evaluation techniques. We have multiple clustering algorithms available in theory and many more implementations available in practice. Clustering is the most widely used unsupervised machine learning technique, having extensive applications in statistical analysis.
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