An Efficient Approach for Computing Silhouette Coefficients
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Copyright: © 2020 Moh'd B. Al- Zoubi and Mohammad al Rawi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
One popular approach for finding the best number of clusters (K) in a data set is through computing the silhouette coefficients. The silhouette coefficients for different values of K, are first found and then the maximum value of these coefficients is chosen. However, computing the silhouette coefficient for different Ks is a very time consuming process. This is due to the amount of CPU time spent on distance calculations. A proposed approach to compute the silhouette coefficient quickly had been presented. The approach was based on decreasing the number of addition operations when computing distances. The results were efficient and more than 50% of the CPU time was achieved when applied to different data sets.
- Silhouette coefficients
- data mining
- pattern recognition