Sentence examples for by cluster analysis based from inspiring English sources

While, the third cluster was represented by populations 3, 4, 5, 6, and 7 (Figure 2). Figure 2 Dendrogram obtained by cluster analysis based on Euclidean distance performed on the essential oil compounds of altitudinal A. herba-alba populations.

Finally, the expression profiles of the differentially expressed genes were determined by cluster analysis based on the SOTA method using Pearson's correlation distance.

In this study, individuals were grouped according to their overall dietary patterns by cluster analysis based on methods used in previous studies [ 21, 22].

The probe sets obtained were finally used for grouping by cluster analysis based on Spearman's rank correlation with average linkage and confidence levels determined by boot-strapping.

In this study, individuals were grouped according to their overall dietary patterns by cluster analysis, based on previous methods (Newby et al., 2003).

Turk et al [ 3] showed that subgroups identified by cluster analysis, based on the Multidimensional Pain Inventory (MPI), could be applicable to FM patients; this subgrouping was based on psychosocial and cognitive characteristics.

That was because clustering of markers was very stable with the large number of tumors (i.e., excluding a few tumors did not substantially influence results) while tumor classification by clustering analysis based on the 16 markers was not stable.

To achieve this, we applied the approach successfully used by Lukes et al. [ 52], in which the patients are divided into two groups by clustering analysis based on the overall expression of the signature genes.

The trends revealed by principal coordinate analysis were supported by UPGMA cluster analysis based on Jaccard's similarity matrix (Figure 6).

We are interested in clustering married women, by using cluster analysis, based on similarities with respect to the individual-level socio-economic and socio-cultural characteristics.

The aims of this study were (1) to classify collected Kansei words into a set of Kansei attributes by using cluster analysis based on fuzzy relations; (2) to model Kansei preferences based on semantic labels for the priority analysis; and (3) to synthesize priority information and rank the order of decision alternatives by means of the linguistic aggregation operation.