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Ward's method joins clusters to maximize the likelihood at each level of the hierarchy under the assumptions of multivariate normal mixtures, spherical covariance matrices, and equal sampling probabilities.
Because incompatible full sibling groups are less likely than incompatible half-sibling groups of the same size, at each similarity step SibJoin joins clusters which form valid full sibships first.
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The process of forming and joining clusters is repeated until a single cluster containing all the samples is obtained.
In fact, in this case the perspective distortion does not change significantly among the joined clusters and the error introduced can be considered negligible.
However, this situation does not represent a problem when the joined clusters refer to groups of people which are at the same distance from the camera.
(c) Ward's method and Bootstrap re-sampling of Ward's method: The objective of Ward's method is to minimize the information lost in clustering by joining clusters resulting in minimum error sum of square.
Average linkage is exploited to join clusters.
SibJoin uses a variant of single linkage clustering to join clusters.
At each step, the joined clusters are those maximizing the average gain.
These sets were then compared with 1642 reference prokaryotic genomes to expand and join clusters.
Most of the joined clusters (3,122) were created from two clusters while three clusters were combined 456 times.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com