Sentence examples for mean silhouette width from inspiring English sources

The higher is the value of the mean silhouette width; the better is the quality of classification.

In this figure, the quality of the classification (measured by the mean silhouette width) is dependent on the number of classes chosen.

The optimal number of groups was selected via two common metrics that quantify the tightness of clustering by considering the distance between samples within a group and the inter-group distance: mean silhouette width and k-nearest neighbor distances.

The mean value from the Silhouette calculations for all data points in each cluster yield an "average Silhouette width" for the cluster.

The ten deciphered signatures are very reproducible (average silhouette width >0.96, Experimental Procedures) as well as extremely similar (average cosine similarity >0.98, see below) to the ones used to generate the 100 mutational catalogs.

This measure, named Fuzzy Silhouette, is a generalization to the fuzzy case of the Average Silhouette Width Criterion, originally conceived to assess crisp (non-fuzzy) data partitions.

Each of them consistently chose a cluster of size two with an average silhouette width ranging between 0.74 and 0.77.

It can be seen from figure 8 that the average silhouette width is highest for the cluster of size 2 with an average of 0.77.

As the number of clusters is increased, the strength of some of the individual groups seems to increase, but the average silhouette width decreases.

The average silhouette width is 0.18 in Verhaak et al., and our CNAR datasets yielded a silhouette width of 0.52.

An average silhouette width of 1.00 is equivalent to consistently deciphering the same mutational signature, whereas a low silhouette width indicates lack of reproducibility of the solution.