Suppose that using the centroid method you found the best location for a communications tower. The location happens to be in the middle of a pond. Then, you should locate the tower.

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Suppose that using the centroid method you found the best location for a communications tower. The location happens to be in the middle of a pond. Then, you should locate the tower after considering qualitative factors such as geography, roads and utilities to help find the exact location

What is the centroid method?

Agglomerative clustering techniques such as the centroid approach identify similarities (or differences) between clusters in terms of their centroids, or multidimensional means, for the variables that were employed in the clustering. Each integer in a vector that makes up a centroid represents the mean value of each variable for the observations in a given cluster. The cluster's multi-dimensional average, or centroid, can be considered. A classification model in machine learning known as a nearest centroid classifier or nearest prototype classifier labels observations with the name of the class of training samples whose mean (centroid).

Hence, Suppose that using the centroid method you found the best location for a communications tower. The location happens to be in the middle of a pond. Then, you should locate the tower after considering qualitative factors such as geography, roads and utilities to help find the exact location

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