Sentence examples for cluster splitting from inspiring English sources

In more detail, the first-pass involves a bottom-up clustering mechanism, the second-pass comprises a cluster splitting operation and the third-pass consists of a cluster refining process.

Algorithm 4 shows the Cluster Splitting Mechanism.

The smaller clustering structure resulting from the cluster splitting schemes in EnLOSC will narrow those gaps, which can reduce the probability of those nodes not being in any one cluster.

The Cluster Merging Mechanism is illustrated in Algorithm 3. The main idea of our Cluster Splitting Mechanism is that the cluster head will start to inform some members to become new cluster heads when it meets all the following conditions: (1) the cluster size is beyond the maximum value and (2) the node density in the radius range of the cluster head is high.

We then tested a cluster splitting algorithm, as follows: b) variants of the cluster were generated, and in each variant one identifier was deleted; the variant was then re-clustered (described above in Initial record linkage) performed.

d) We scored the cluster splitting as successful if the identifier picked for deletion on the basis that it was bad in step (c) was the same 'bad' identifier selected in step (a).

Synaptophysin clusters were scored as "stable clusters" if they did not move more than 2 µm over the entire image acquisition period or "splitting" if a single cluster split into 2 separate clusters.

We also propose two partition methods based on sampling results: cluster combination and cluster split combination.

Second, we propose a new distance measure for ER (called 'mergee distance") inspired by the edit distance of strings, using cluster splits and merges as its basic operations.

Second, we explore a new distance measure for ER (called ''generalized merge distance" or $GMD$) inspired by the edit distance of strings, using cluster splits and merges as its basic operations.

The cluster splits up in two parts.