Summary
■ In conventional cluster analysis, an object is assigned to one cluster exclusively. However, in some applications, there is a need to assign an object to one or more clusters in a fuzzy or probabilistic way. Fuzzy clustering and probabilistic model-based clustering allow an object to belong to one or more clusters. A partition matrix records the membership degree of objects belonging to clusters.
■ Probabilistic model-based clustering assumes that a cluster is a parameterized distribution. Using the data to be clustered as the observed samples, we can estimate the parameters of the clusters.
■ A mixture model assumes that a set of observed objects is a mixture of instances from multiple probabilistic clusters. Conceptually, each observed ...
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