cluster man page on Oracle

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CLUSTER(1)							    CLUSTER(1)

       cluster	-  find	 clusters  in  a graph and augment the graph with this

       cluster [-v?]  [ -Ck ] [ -ck ] [ -o outfile ] [ files ]

       cluster takes as input a graph in DOT format, finds node	 clusters  and
       augments	 the  graph with this information.  The clusters are specified
       by the "cluster" attribute attached to nodes; cluster values  are  non-
       negative	 integers.  cluster attempts to maximize the modularity of the
       clustering.  If the edge attribute "weight" is defined,	this  will  be
       used in computing the clustering.

       The following options are supported:

       -Ck    specifies	 a  targeted  number of clusters that should be gener‐
	      ated.  The specified number k is only a suggestion and  may  not
	      be  realisable.	If k == 0, the default, the number of clusters
	      that approximately optimizes the modularity is returned.

       -ck    specifies clustering method.  If k == 0, the default, the	 modu‐
	      larity will be used. If k == 1 modularity quality will be used.

	      Specifies	 that  output  should  go  into	 the  file outfile. By
	      default, stdout is used.

       -v     Verbose mode.

       Applying cluster to the following graph,

	  graph {
	      1--2 [weight=10.]
	      2--3 [weight=1]
	      3--4 [weight=10.]
	      4--5 [weight=10]
	      5--6 [weight=10]
	      3--6 [weight=0.1]
	      4--6 [weight=10.]


	  graph {
		node [cluster="-1"];
		1 [cluster=1];
		2 [cluster=1];
		3 [cluster=2];
		4 [cluster=2];
		5 [cluster=2];
		6 [cluster=2];
		1 -- 2 [weight="10."];
		2 -- 3 [weight=1];
		3 -- 4 [weight="10."];
		4 -- 5 [weight=10];
		5 -- 6 [weight=10];
		3 -- 6 [weight="0.1"];
		4 -- 6 [weight="10."];

       Yifan Hu <>


       Blondel, V.D., Guillaume,  J.L.,	 Lambiotte,  R.,  Lefebvre,  E.:  Fast
       unfolding  of  communities  in  large  networks. Journal of Statistical
       Mechanics: Theory and Experiment (2008), P10008.

				 3 March 2011			    CLUSTER(1)

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