Re: Clustering
- To: mathgroup at smc.vnet.net
- Subject: [mg127982] Re: Clustering
- From: Murta <rodrigomurtax at gmail.com>
- Date: Fri, 7 Sep 2012 04:55:49 -0400 (EDT)
- Delivered-to: l-mathgroup@mail-archive0.wolfram.com
- Delivered-to: l-mathgroup@wolfram.com
- Delivered-to: mathgroup-newout@smc.vnet.net
- Delivered-to: mathgroup-newsend@smc.vnet.net
- References: <k29mfn$ace$1@smc.vnet.net>
Hi.. there is one solutions data1 = yourData r = ClusteringComponents[Sort@data1, 4, Method -> "KMeans"]; ListPlot[Pick[Sort@data1, r, #] & /@ Range[4]] I used sort just to be more visual. ClusteringComponents has more options then FindCluster. best Regards Murta On Thursday, September 6, 2012 5:23:23 AM UTC-3, Nigel King wrote: > 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=