Sentence examples for clusters we used from inspiring English sources

To choose the number of clusters, we used the average silhouette index [39].

To create the clusters we used both name and email; we first normalized the names, then we looked for name similarities, name-email similarities, and email similarities.

For the modelling of the operation of these clusters, we used registered time series of the years 2011 and 2012 for a total load and feed-in from wind and solar PV, which were projected for the year 2022.

In order to simulate overlapped clusters, we used CircleCluster function that generates uniformly distributed data within a circle seen as a cluster, as follows: Randomly generate the center of the clusters.

To visualize the connectivity among clusters, we used Visone [58].

Additionally for analyzing enrichment in SOM clusters, we used the Database for Annotation, Visualization and Integrated Discovery (DAVID) [6], [55].

Focussing on these two major clusters, we used DAVID software (Table S2) to conduct a gene ontogeny analysis [20], [21].

Since the competing algorithms cannot detect the number of clusters, we use the value from the ground truth.

To find an optimal threshold on the number of clusters, we use the Silhouette method, which compares the tightness and separation of clusters [42].

To validate clusters, we use the Silhouette width [ 12] to measure their validity.

To generate QD clusters, we use a technique invented by Pease [ 26].