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The mean values of data points in clusters are used to measure cluster similarities and MapReduce computes distances between data points simultaneously.
However, we succeeded to find minute pyramid and wedge at this h Ge (Figure 3d --both as small as 2 ML over the patch surface (we measure cluster heighs from patch tops)--which indicate that hut nucleation had started a little earlier.
We measure cluster quality using a textual coherence measure based on the Jensen-Shannon divergence [27], and using concentration measures based on the grant-to-article linkages indexed in MEDLINE.
To measure cluster tightness, we used homogeneity, and to measure cluster separation and structure we used the average silhouette, both are described in detail in the Methods section.
In FBPA, we used within-method clustering metrics to measure cluster homogeneity and separation.
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The analysts then ran a statistical test to measure clustering between regions of similar word preference.
Moran's I statistics are calculated to measure clustering within both social and spatial matrices.
We use topic distributions to measure clustering among formally recognized crime types.
There are several ways to measure clustering quality: intrinsic methods (by measuring the proximity of elements inside a cluster and the proximity between clusters) and extrinsic methods that use manual ground truth classification.
Local HMM-HMM alignment routine provided by HH-suite (Soding, 2004) is used to measure cluster-cluster similarity.
Finally, we used spatial statistics to measure clustering of neighborhoods with similar HVI index scores.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com