Sentence examples for evaluated cluster from inspiring English sources

Jaccard coefficients close to zero indicate low similarities and values close to one indicate high similarities among the evaluated cluster sets.

The Jaccard index is a commonly used similarity measure for comparing clustering results, where values close to 0 indicate low similarities and values closer to 1 higher similarities among the evaluated cluster sets.

The ALR preserves the martingale structure of the regular likelihood ratio, which allows the determination of an upper limit for the false alarm rate, depending only on the quantity of evaluated cluster candidates.

We evaluated clustering using multi-dimensional scaling and AMOVA methods [43], maximizing the between-group variation (vA) and minimizing the within-group variation (vB).

To bracket this definition of an avian community, we also evaluated clusters with 20 and 100 groups (Figs. S3 and S4).

We evaluated cluster-number metric performance of three simulated datasets which had four, six and eight clusters, respectively.

We evaluated clusters using 999 Monte Carlo simulations.

In this experiment, six users evaluated clustering quality for the query 'metastasis or metastatic'.

We evaluated clusters H03 and H33 as a single cluster because they differ in only 1 band by IS 6110 RFLP.

Because there is no correct solution to unsupervised machine learning tasks, we evaluated clustering solutions based on their interpretability in the domain of the epithelial-mesenchymal transition.

With these ground truth datasets in hand, we evaluated clustering accuracy using the Jaccard coefficient as described by Tan et al. (2005).