Applied Science
Comparison of Clustering Algorithms: K-Means, DBSCAN & Ward’s method
Several clustering algorithms have been introduced to literature in the last 10 years. Clustering methods usage depends on their complexity, the amount of data, the purpose of clustering and the predefined parameters. This case study, presents three of the most used clustering algorithms, K-means, DBSCAN and Ward’s method. K-means K-means Read more…