Sentence examples for clustered such that from inspiring English sources

Large datasets must be clustered such that every other entity or data point in the cluster is similar to any other entity in the same cluster.

When the eavesdropper is restricted to overhearing on the channel from the source and the relay to the destination, our bound is tight for a subclass of channels where the source and the relay are clustered such that the combined link from the source and the relay to the destination is the bottleneck.

Additionally, miRNAs are frequently clustered such that a single pri-miRNA contains multiple miRNA sequences.

The weight matrices were clustered such that each cluster of weight matrices can be regarded as non-redundant (see the Methods section).

Subsequently, the age-regulated probes were clustered such that major age-dependent expression trends could be identified (outlined in Figure  1).

If elements are clustered such that they are separable by another shape in N-space (e.g., a hypersphere), then an appropriate transform of the hyperspace to another space will make them separable by a hyperplane.

Experimental results support our claim on the feasibility of privacy-preserving K-means clustering such that it takes 26 min to cluster 100,000 users.

The first and most challenging step in this process is configuring k-means clustering such that it effectively identifies subtle trends such as phase boundaries, domain walls, grain boundaries, dislocations, or cracks and segregates the dataset accordingly.

Gene expression data were normalized prior to clustering such that the expression levels of each gene for each patient had a mean of zero and a standard deviation of one.

There may be other plausible models, for example ones where allele reads exhibit clustering such that observed homozygosity is higher (when depth exceeds one) than in the random reads case, but which still have K = ½ when k = 1.

Clustering is the process of partitioning a given set into c distinct disjoint subsets called clusters such that elements (e.g. reads) on the same cluster have minimum distance between them and maximum distance with elements of different clusters.