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. 2010 Apr 6;11:169. doi: 10.1186/1471-2105-11-169

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Copyright ©2010 Kraus and Kestler; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Example for cluster evaluation via the MCA index. On the left, two possible partitionings of the data set are shown, i. e. P = {A₁, A₂, A₃} and Q = {B₁, B₂, B₃}. The bipartite matching graph is given on the right. Each edge is annotated with the number of intersecting data points in both partitionings. The solid lines mark the maximal matching edges. In this example the MCA index is = 0.71.

Inline graphic — Example for cluster evaluation via the MCA index. On the left, two possible partitionings of the data set are shown, i. e. P = {A₁, A₂, A₃} and Q = {B₁, B₂, B₃}. The bipartite matching graph is given on the right. Each edge is annotated with the number of intersecting data points in both partitionings. The solid lines mark the maximal matching edges. In this example the MCA index is = 0.71.