Silhouette width using generalized mean-A flexible method for assessing clustering efficiency.

ABSTRACT: Cluster analysis plays vital role in pattern recognition in several fields of science. Silhouette width is a widely used index for assessing the fit of individual objects in the classification, as well as the quality of clusters and the entire classification. Silhouette combines two clustering criteria, compactness and separation, which imply that spherical cluster shapes are preferred over others-a property that can be seen as a disadvantage in the presence of complex, nonspherical clusters, which is common in real situations. We suggest a generalization of the silhouette width using the generalized mean. By changing the p parameter of the generalized mean between -∞ and +∞, several specific summary statistics, including the minimum, maximum, the arithmetic, harmonic, and geometric

SUBMITTER: Lengyel A 

PROVIDER: S-EPMC6912895 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature