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cluster per area vs clustering per area

Both phrases are correct, but they have slightly different meanings. 'Cluster per area' refers to the number of clusters in a specific area, while 'clustering per area' refers to the process of clustering data points within a particular area. They are not directly comparable as they serve different purposes.

Last updated: March 15, 2024 • 438 views

cluster per area

This phrase is correct and commonly used in the context of data analysis to refer to the number of clusters in a specific area.

This phrase is used to describe the quantity of clusters within a particular area or region.

Examples:

The algorithm identified one cluster per area in the dataset.

Show examples from the web [+]

... to an attribute that can split your data in separate area (you won't be able to do cross area search). Then you can have one cluster per area.
Il bando prevede inoltre una dura selettività (sarà selezionato un solo Cluster per area tematica); pertanto per parteciparvi è necessaria la costruzione di ...
CF. Tutto ci`o realizza l'equazione: G = i2 + j2 + ij. Indicando con S lo spettro delle frequenze e M il numero di cluster per area, si definisce la capacit`a della rete:.
16 km and in the north one cluster per area of 24 km × 32 km. Only sample plots with the required forest site attributes were included. Of 3009 sample plots ...

Alternatives:

number of clusters per area
cluster density in each area

clustering per area

This phrase is also correct and commonly used in the context of data analysis to describe the process of clustering data points within a specific area.

This phrase is used to explain the process of grouping data points into clusters within a particular area or region.

Examples:

The algorithm is performing clustering per area to identify patterns in the data.

Show examples from the web [+]

OpenSSL Support for Client-Server and Point-to-Point; ZLib Support for Client- Server and Point-to-Point; Standby server; Clustering per area(s). MySQL support :.

Alternatives:

data clustering within an area
clustering within specific regions

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