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docs/comparing_clustering_algorithms.rst

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@@ -552,7 +552,7 @@ of a cluster'. This results in a smaller tree with fewer clusters that
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'lose points'. That tree can then be used to select the most stable or
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persistent clusters. This process allows the tree to be cut at varying
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height, picking our varying density clusters based on cluster stability.
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The immediate advantage of this is that we can ave varying density
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The immediate advantage of this is that we can have varying density
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clusters; the second benefit is that we have eliminated the epsilon
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parameter as we no longer need it to choose a cut of the dendrogram.
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Instead we have a new parameter ``min_cluster_size`` which is used to

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