K-means clustering: how it works

Автор: Victor Lavrenko

Загружено: 2014-01-19

Просмотров: 866769

Описание: Full lecture: http://bit.ly/K-means
The K-means algorithm starts by placing K points (centroids) at random locations in space. We then perform the following steps iteratively: (1) for each instance, we assign it to a cluster with the nearest centroid, and (2) we move each centroid to the mean of the instances assigned to it. The algorithm continues until no instances change cluster membership.

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K-means clustering: how it works

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