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Clustering

• To: mathgroup at smc.vnet.net
• Subject: [mg127967] Clustering
• From: Nigel King <nigel.king at cambiumnetworks.com>
• Date: Thu, 6 Sep 2012 04:13:14 -0400 (EDT)
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• Delivered-to: l-mathgroup@wolfram.com
• Delivered-to: mathgroup-newout@smc.vnet.net
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Hi All,
The following short program has some data which looks visually as though it would separate into 4 groups by the use of the command FindClusters. You can see the use of that command in the lines below but, the data has not separated as I would have expected. I realise that I do not know how to use the various clustering components of mathematica to do this. Any insight would be useful.

Thanks

Nigel King


data1 = {10996160116271, 10996160121402, 10996159625418, 10996162114125,
   10996160124050, 10996162119731, 10996162119161, 10996162119412,
   10996159624663, 10996159625205, 10996162082868, 10996159624249,
   10996162084724, 10996162091672, 10996162117101, 10996162100233,
   10996162119612, 10996163806869, 10996162119594, 10996160176675,
   10996160176687, 10996160176724, 10996160176645, 10996162120528,
   10996160157953, 10996160147558, 10996160159628, 10996160158103,
   10996160153768, 10996160158093, 10996160147558, 10996162118276,
   10996162119018, 10996163808057, 10996163808139, 10996163807032,
   10996162122560, 10996162068604, 10996162127032, 10996162119426,
   10996162119433, 10996162119039, 10996162119429, 10996162118843,
   10996162119436, 10996162120269, 10996162119583, 10996162120271,
   10996162120255, 10996162119663, 10996162064880, 10996162120272,
   10996162120224, 10996162119666, 10996163810937, 10996162118985,
   10996162119234, 10996160158214, 10996163810862, 10996162119390,
   10996162119218, 10996162119211, 10996162119144, 10996162119264,
   10996162119046, 10996162119267, 10996162120316, 10996162119425,
   10996162119536, 10996162119071, 10996162119346, 10996162120402,
   10996162119091, 10996162119030, 10996162119499, 10996162115558,
   10996162119337, 10996162119035, 10996162119534, 10996162117042,
   10996162119215, 10996162119393, 10996162118962, 10996159624797,
   10996162120344, 10996162119377, 10996162120222, 10996162120223,
   10996162119407, 10996162120246, 10996162120279, 10996162120326,
   10996162119994, 10996162120057, 10996162120294, 10996162119880,
   10996162119513, 10996162119803, 10996160145836, 10996160136827,
   10996162068121, 10996162078289, 10996159618487, 10996159623760,
   10996159624293, 10996160180483, 10996159624759, 10996162118806,
   10996160181693, 10996159623760, 10996159624411, 10996160116463,
   10996159618114, 10996160162419, 10996160160562, 10996160121379,
   10996160125728, 10996160168867, 10996160142681, 10996160168532,
   10996160168551, 10996160150082, 10996159625337, 10996159625454};
clu = FindClusters[data1, 4, Method -> "Optimize"];
plt[v_] :=
 ListPlot[Sort[v] - Median[v], PlotRange -> All, ImageSize -> 300,
  Frame -> True, Axes -> False]
plt[data1]
Map[plt, c1u] // Column=

• Follow-Ups:
  • Re: Clustering
    • From: Nigel King <nigel.king@cambiumnetworks.com>
  • Re: Clustering
    • From: Bob Hanlon <hanlonr357@gmail.com>