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Bayesian cluster analysis : point estimation and credible balls

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Figure 3: Hasse diagram stretched by ˜stretched Hasse diagram, we can determine the distance between any two partitions.Example: ifB with a sample of size N = 4
Figure 4: The data is simulated from a mixture of four normals with locations (±2, ±2)′and colored by cluster membership
Figure 5: Clustering estimate with color representing cluster membership for Binder’sloss (first row) and VI (second row) with columns corresponding to examples.
Table 1: A comparison of the clustering estimate with ˜of clustersB or VI in terms of 1) number k∗N; 2) number of data points incorrectly classified, denoted NI; 3) expected˜B; 4) ˜B between the optimal and true clusterings; 5) expected lower bound of VI; 6)expected VI; and 7) VI between the optimal and true clusterings for both examples.
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