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Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters).
Next: Hierarchical Classifiers Up: classification Previous: Some special cases Unsupervised Classification - Clustering. A clustering algorithm groups the given samples, each represented as a vector in the N-dimensional feature space, into a set of clusters according to their spatial distribution in the N-D space. Clustering is an unsupervised classification as no a priori knowledge (such as samples of known classes) is assumed to be available. The K-Means Algorithm. Step 1. Randomly choose initial cluster centers from the given sample set (e.g., the first samples of the sample set). Set ; Step 2.