Sentence examples for cluster approach that from inspiring English sources

Hierarchical clustering is a well established cluster approach that starts by considering each compound as a single cluster and subsequently merges two clusters at a time.

However, one should keep in mind that their analysis was based on an inferior cluster approach that led, from a biological point of view, to a number of wrongly assigned clusters.

HEED is a distributed clustering approach that operates in energy efficient manner and helps in prolonging network lifetime.

This framework is based on the recently developed property clustering approach that allows one to perform design calculations on a component-free (or composition-free) basis.

In contrast to this, we do not consider workloads but a generic clustering approach that can work with arbitrary workloads providing the feature of flexible query answering by finding semantically related answers.

However, as a user may visit new places over time and we do not know a priori the total number of places a user may visit, we chose to employ a density‐based clustering approach that can incrementally adapts the number of clusters (i.e., the number of unique physical locations) in our system.

However, as a user may visit new places over time and we do not know a priori the total number of places a user may visit, we chose to use a density-based clustering approach that can incrementally adapts the number of clusters (i.e., the number of distinct physical locations).

We first used the COG-04 dataset (see Methods) to compare the the extended Psi-square algorithm with our hierarchical clustering approach that used the same data [15].

The Bayesian clustering approach that was developed to identify genetic structure in the mixed populations has often been applied to test for the presence of a taxon without assigning individuals to a predefined group [25], [27], [29], [72].

We therefore repeated the classification of phylogenetic distribution using a clustering approach that groups similar transcripts both within and between species.

As a byproduct of our analysis, we can also make conclusions about individual clustering algorithms: overall, though there are some clustering approaches which clearly outperform others, there is no single network clustering approach that dominates the rest in all cases.