Estimating the Cluster Tree of a Density

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Estimating the Cluster Treeof a Density Werner
StuetzleRebecca Nugent Department of
StatisticsUniversity of Washington
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Groups
K-means with k 2
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• Detect that there are 5 or 6 distinct groups.
• Assign group labels to observations.

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Note large tree fragments in bottom left panel
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Runt Pruning algorithm generate_cluster_tree_node
(mst, runt_size_threshold) node
new_cluster_tree_node node.leftson
node.rightson NULL node.obs leaves
(mst) cut_edge longest_edge_with_large_run
t_size (mst, runt_size_threshold) if
(cut_edge) node.leftson
generate_cluster_tree_node (left_subtree
(cut_edge), runt_size_threshold)
node.rightson generate_cluster_tree_node
(right_subtree (cut_edge), runt_size_threshold)
return (node)
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Note large tree fragments in bottom left panel
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Runt Pruning algorithm generate_cluster_tree_node
(mst, runt_size_threshold) node
new_cluster_tree_node node.leftson
node.rightson NULL node.obs leaves
(mst) cut_edge longest_edge_with_large_run
t_size (mst, runt_size_threshold) if
(cut_edge) node.leftson
generate_cluster_tree_node (left_subtree
(cut_edge), runt_size_threshold)
node.rightson generate_cluster_tree_node
(right_subtree (cut_edge), runt_size_threshold)
return (node)