کامپیوتر و شبکه::
Girls Dance with Girls, Boys Scratch their Elbows Getting Real: K-Means Clustering Subscribers in E-mail Marketing
This chapter looks at the most common type of clustering, called k-means clustering, which originated in the 1950s and has since become a go-to clustering technique for knowledge discovery in databases (KDD) across industries and the government.
The goal in k-means clustering is to take some points in space and put them into k groups (where k is any number you want to pick).
Now, k-means clustering demands that you specify how many clusters you want to put the attendees in.
In k-means clustering, dancers are assigned to the cluster that's nearest them, so between any two cluster centers on the floor, you can draw a line of demarcation, whereby if a dancer is on one side of the line they're in one group, but if they're on the other side, their group changes (see Figure 2.3).
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