Quantitative Techniques PPT File
The K-means algorithm divides a single cluster into K different clusters. It does this by finding organically similar data points and assigning each one to a cluster with similar characteristics. K-means clustering works by constantly trying to find a centroid (a data point that represents the mean or centre of the cluster). The end clusters will each have a centroid and data points that are closer to the centroid compared to the other centroids.
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