Thanks, Martin! ...Tao
> From: maech...@stat.math.ethz.ch > Date: Wed, 13 May 2009 14:13:48 +0200 > To: shi...@hotmail.com > CC: rip...@stats.ox.ac.uk; bcarv...@jhsph.edu; r-help@r-project.org; > maech...@stat.math.ethz.ch > Subject: Re: [R] silhouette: clustering labels have to be consecutive > integers starting > > >>>>> "TS" == Tao Shi <shi...@hotmail.com> > >>>>> on Wed, 10 Oct 2007 06:15:53 +0000 writes: > > TS> Thank you very much, Benilton and Prof. Ripley, for the > TS> speedy replies! > > TS> Looking forward to the fix! > TS> ....Tao > > I have finally re-stumbled onto this e-mail thread, > and indeed found fixed the problem. > > Version 1.12.0 of 'cluster' should become visible within a few days, > and will allow to call > > silhoutte(g, dis) > > on a grouping vector of k different integer values which need > *not* necessarily be in 1:k. > > Martin Maechler, > ETH Zurich > > > >> From: Prof Brian Ripley <rip...@stats.ox.ac.uk> > >> To: Benilton Carvalho <bcarv...@jhsph.edu> > >> CC: Tao Shi <shi...@hotmail.com>, maech...@stat.math.ethz.ch, > >> r-help@r-project.org > >> Subject: Re: [R] silhouette: clustering labels have to be consecutive > >> intergers starting from 1? > >> Date: Wed, 10 Oct 2007 05:33:03 +0100 (BST) > >> > >> It is a C-level problem in package cluster: valgrind gives > >> > >> ==11377== Invalid write of size 8 > >> ==11377== at 0xA4015D3: sildist (sildist.c:35) > >> ==11377== by 0x4706D8: do_dotCode (dotcode.c:1750) > >> > >> This is a matter for the package maintainer (Cc:ed here), not R-help. > >> > >> On Tue, 9 Oct 2007, Benilton Carvalho wrote: > >> > >>> that happened to me with R-2.4.0 (alpha) and was fixed on R-2.4.0 > >>> (final)... > >>> > >>> http://tolstoy.newcastle.edu.au/R/e2/help/06/11/5061.html > >>> > >>> then i stopped using... now, the problem seems to be back. The same > >>> examples still apply. > >>> > >>> This fails: > >>> > >>> require(cluster) > >>> set.seed(1) > >>> x <- rnorm(100) > >>> g <- sample(2:4, 100, rep=T) > >>> for (i in 1:100){ > >>> print(i) > >>> tmp <- silhouette(g, dist(x)) > >>> } > >>> > >>> and this works: > >>> > >>> require(cluster) > >>> set.seed(1) > >>> x <- rnorm(100) > >>> g <- sample(2:4, 100, rep=T) > >>> for (i in 1:100){ > >>> print(i) > >>> tmp <- silhouette(as.integer(factor(g)), dist(x)) > >>> } > >>> > >>> and here's the sessionInfo(): > >>> > >>> > sessionInfo() > >>> R version 2.6.0 (2007-10-03) > >>> x86_64-unknown-linux-gnu > >>> > >>> locale: > >>> > LC_CTYPE=en_US.UTF-8;LC_NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_US.U > >>> > TF-8;LC_MONETARY=en_US.UTF-8;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF- > >>> > 8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_ID > >>> ENTIFICATION=C > >>> > >>> attached base packages: > >>> [1] stats graphics grDevices utils datasets methods base > >>> > >>> other attached packages: > >>> [1] cluster_1.11.9 > >>> > >>> > >>> (Red Hat EL 2.6.9-42 smp - AMD opteron 848) > >>> > >>> b > >>> > >>> On Oct 9, 2007, at 8:35 PM, Tao Shi wrote: > >>> > >>>> Hi list, > >>>> > >>>> When I was using 'silhouette' from the 'cluster' package to > >>>> calculate clustering performances, R crashed. I traced the problem > >>>> to the fact that my clustering labels only have 2's and 3's. when > >>>> I replaced them with 1's and 2's, the problem was solved. Is the > >>>> function purposely written in this way so when I have clustering > >>>> labels, "2" and "3", for example, the function somehow takes the > >>>> 'missing' cluster "2" into account when it calculates silhouette > >>>> widths? > >>>> > >>>> Thanks, > >>>> > >>>> ....Tao > >>>> > >>>> ##============================================ > >>>> ## sorry about the long attachment > >>>> > >>>>> R.Version() > >>>> $platform > >>>> [1] "i386-pc-mingw32" > >>>> > >>>> $arch > >>>> [1] "i386" > >>>> > >>>> $os > >>>> [1] "mingw32" > >>>> > >>>> $system > >>>> [1] "i386, mingw32" > >>>> > >>>> $status > >>>> [1] "" > >>>> > >>>> $major > >>>> [1] "2" > >>>> > >>>> $minor > >>>> [1] "5.1" > >>>> > >>>> $year > >>>> [1] "2007" > >>>> > >>>> $month > >>>> [1] "06" > >>>> > >>>> $day > >>>> [1] "27" > >>>> > >>>> $`svn rev` > >>>> [1] "42083" > >>>> > >>>> $language > >>>> [1] "R" > >>>> > >>>> $version.string > >>>> [1] "R version 2.5.1 (2007-06-27)" > >>>> > >>>>> library(cluster) > >>>>> cl1 ## clustering labels > >>>> [1] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 > >>>> [30] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 > >>>> [59] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 > >>>> [88] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 > >>>> [117] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 > >>>> [146] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 > >>>> [175] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 > >>>> [204] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 > >>>>> x1 ## 1-d input vector > >>>> [1] 1.5707963 1.5707963 1.5707963 1.5707963 1.5707963 > >>>> [6] 1.5707963 1.5707963 1.5707963 1.5707963 1.5707963 > >>>> [11] 1.5707963 1.5707963 1.5707963 1.5707963 1.5707963 > >>>> [16] 1.5707963 1.5707963 1.5707963 1.5707963 1.5707963 > >>>> [21] 1.0163758 0.7657763 0.7370084 0.6999689 0.7366476 > >>>> [26] 0.7883921 0.6925395 0.7729240 0.7202391 0.7910149 > >>>> [31] 0.7397698 0.7958092 0.6978596 0.7350255 0.7294362 > >>>> [36] 0.6125713 0.7174000 0.7413046 0.7044205 0.7568104 > >>>> [41] 0.7048469 0.7334515 0.7143170 0.7002311 0.7540981 > >>>> [46] 0.7627527 0.7712762 0.8193611 0.7801148 0.9061762 > >>>> [51] 0.8248195 0.7932630 0.7248037 0.7423547 0.6419314 > >>>> [56] 0.6001092 0.7572272 0.7631742 0.7085384 0.8710853 > >>>> [61] 0.6589563 0.7464943 0.7487340 0.7751280 0.7946542 > >>>> [66] 0.7666081 0.8508109 0.8314308 0.7442471 0.8006093 > >>>> [71] 0.7949156 0.7852447 0.7630048 0.7104764 0.6768218 > >>>> [76] 0.6806351 0.7255355 0.7431389 0.7523627 0.7670515 > >>>> [81] 0.8118214 0.7215615 0.8186164 0.6941610 0.8285453 > >>>> [86] 0.8395170 0.8088044 0.8182706 0.7550723 0.7948639 > >>>> [91] 0.7204830 0.7109068 0.7756949 0.6837856 0.7055604 > >>>> [96] 0.6126666 0.7201964 0.6849890 0.7779753 0.7845284 > >>>> [101] 0.9370788 0.8242935 0.6908860 0.6446151 0.7660386 > >>>> [106] 0.8141526 0.8111984 0.8624186 0.7865335 0.8213035 > >>>> [111] 0.8059171 0.6735751 0.7815353 0.6972508 0.6699396 > >>>> [116] 0.6293971 0.7475913 0.7700821 0.8258339 0.8096144 > >>>> [121] 0.7058171 0.7516635 0.7323909 0.7229136 0.8344846 > >>>> [126] 0.7205433 0.8287774 0.8322097 0.7767547 0.7402277 > >>>> [131] 0.7939879 0.7797308 0.7112453 0.7091554 0.6417382 > >>>> [136] 0.6369171 0.7059020 0.7496380 0.7298359 0.8202566 > >>>> [141] 0.7331830 0.7344492 0.8316894 0.7323979 0.7977615 > >>>> [146] 0.7841205 0.7587060 0.8056685 0.7895643 0.8140731 > >>>> [151] 0.7890221 0.8016008 0.7381577 0.6936453 0.7133525 > >>>> [156] 0.7121459 0.6851448 0.7946275 0.8077618 0.7899059 > >>>> [161] 0.7128826 0.7546289 0.7042451 0.6606403 0.7525233 > >>>> [166] 0.7527548 0.8098887 0.8254190 0.7873064 0.8139340 > >>>> [171] 0.7903462 0.8377651 0.6709983 0.7423632 0.6632082 > >>>> [176] 0.5676717 0.6925125 0.7077083 0.7488877 0.7630604 > >>>> [181] 0.7843001 0.7524471 0.6871823 0.7144443 0.7692206 > >>>> [186] 0.8690710 0.9282786 0.7844991 0.7094671 0.7578409 > >>>> [191] 0.8026643 0.7759241 0.6997376 0.6167209 0.6682289 > >>>> [196] 0.6572018 0.7615807 0.7415752 0.7659161 0.7040360 > >>>> [201] 0.6874460 0.7052109 0.8290970 0.6915149 0.7173107 > >>>> [206] 0.7848961 0.7943846 0.8437946 0.7817344 0.8867006 > >>>> [211] 0.7575857 0.8390473 0.7382348 0.6789859 0.7129010 > >>>> [216] 0.6938173 0.7384170 0.6747648 0.7203337 0.7278963 > >>>>> silhouette(cl1, dist(x1)^2) ##### CRASHED! ###### > >>>>> silhouette(ifelse(cl1==3,2,1), dist(x1)^2) > >>>> cluster neighbor sil_width > >>>> [1,] 2 1 1.0000000 > >>>> [2,] 2 1 1.0000000 > >>>> [3,] 2 1 1.0000000 > >>>> [4,] 2 1 1.0000000 > >>>> [5,] 2 1 1.0000000 > >>>> [6,] 2 1 1.0000000 > >>>> [7,] 2 1 1.0000000 > >>>> [8,] 2 1 1.0000000 > >>>> [9,] 2 1 1.0000000 > >>>> [10,] 2 1 1.0000000 > >>>> [11,] 2 1 1.0000000 > >>>> [12,] 2 1 1.0000000 > >>>> [13,] 2 1 1.0000000 > >>>> [14,] 2 1 1.0000000 > >>>> [15,] 2 1 1.0000000 > >>>> [16,] 2 1 1.0000000 > >>>> [17,] 2 1 1.0000000 > >>>> [18,] 2 1 1.0000000 > >>>> [19,] 2 1 1.0000000 > >>>> [20,] 2 1 1.0000000 > >>>> [21,] 1 2 0.7592857 > >>>> [22,] 1 2 0.9934455 > >>>> [23,] 1 2 0.9937880 > >>>> [24,] 1 2 0.9909544 > >>>> [25,] 1 2 0.9937769 > >>>> [26,] 1 2 0.9912442 > >>>> [27,] 1 2 0.9900156 > >>>> [28,] 1 2 0.9929499 > >>>> [29,] 1 2 0.9929125 > >>>> [30,] 1 2 0.9908637 > >>>> [31,] 1 2 0.9938610 > >>>> [32,] 1 2 0.9900958 > >>>> [33,] 1 2 0.9906993 > >>>> [34,] 1 2 0.9937227 > >>>> [35,] 1 2 0.9934823 > >>>> [36,] 1 2 0.9740954 > >>>> [37,] 1 2 0.9926948 > >>>> [38,] 1 2 0.9938924 > >>>> [39,] 1 2 0.9914623 > >>>> [40,] 1 2 0.9938250 > >>>> [41,] 1 2 0.9915088 > >>>> [42,] 1 2 0.9936633 > >>>> [43,] 1 2 0.9924367 > >>>> [44,] 1 2 0.9909855 > >>>> [45,] 1 2 0.9938891 > >>>> [46,] 1 2 0.9936028 > >>>> [47,] 1 2 0.9930799 > >>>> [48,] 1 2 0.9848568 > >>>> [49,] 1 2 0.9922685 > >>>> [50,] 1 2 0.9371272 > >>>> [51,] 1 2 0.9832647 > >>>> [52,] 1 2 0.9905154 > >>>> [53,] 1 2 0.9932217 > >>>> [54,] 1 2 0.9939101 > >>>> [55,] 1 2 0.9810071 > >>>> [56,] 1 2 0.9708675 > >>>> [57,] 1 2 0.9938131 > >>>> [58,] 1 2 0.9935827 > >>>> [59,] 1 2 0.9918943 > >>>> [60,] 1 2 0.9628701 > >>>> [61,] 1 2 0.9844965 > >>>> [62,] 1 2 0.9939491 > >>>> [63,] 1 2 0.9939495 > >>>> [64,] 1 2 0.9927610 > >>>> [65,] 1 2 0.9902895 > >>>> [66,] 1 2 0.9933968 > >>>> [67,] 1 2 0.9734481 > >>>> [68,] 1 2 0.9811285 > >>>> [69,] 1 2 0.9939341 > >>>> [70,] 1 2 0.9892304 > >>>> [71,] 1 2 0.9902461 > >>>> [72,] 1 2 0.9916649 > >>>> [73,] 1 2 0.9935909 > >>>> [74,] 1 2 0.9920846 > >>>> [75,] 1 2 0.9876779 > >>>> [76,] 1 2 0.9882868 > >>>> [77,] 1 2 0.9932665 > >>>> [78,] 1 2 0.9939213 > >>>> [79,] 1 2 0.9939182 > >>>> [80,] 1 2 0.9933699 > >>>> [81,] 1 2 0.9868129 > >>>> [82,] 1 2 0.9930074 > >>>> [83,] 1 2 0.9850624 > >>>> [84,] 1 2 0.9902300 > >>>> [85,] 1 2 0.9820895 > >>>> [86,] 1 2 0.9781906 > >>>> [87,] 1 2 0.9875197 > >>>> [88,] 1 2 0.9851569 > >>>> [89,] 1 2 0.9938688 > >>>> [90,] 1 2 0.9902547 > >>>> [91,] 1 2 0.9929304 > >>>> [92,] 1 2 0.9921257 > >>>> [93,] 1 2 0.9927096 > >>>> [94,] 1 2 0.9887702 > >>>> [95,] 1 2 0.9915856 > >>>> [96,] 1 2 0.9741195 > >>>> [97,] 1 2 0.9929094 > >>>> [98,] 1 2 0.9889500 > >>>> [99,] 1 2 0.9924910 > >>>> [100,] 1 2 0.9917552 > >>>> [101,] 1 2 0.9047049 > >>>> [102,] 1 2 0.9834247 > >>>> [103,] 1 2 0.9897916 > >>>> [104,] 1 2 0.9815845 > >>>> [105,] 1 2 0.9934304 > >>>> [106,] 1 2 0.9862375 > >>>> [107,] 1 2 0.9869624 > >>>> [108,] 1 2 0.9677353 > >>>> [109,] 1 2 0.9914973 > >>>> [110,] 1 2 0.9843076 > >>>> [111,] 1 2 0.9881568 > >>>> [112,] 1 2 0.9871393 > >>>> [113,] 1 2 0.9921114 > >>>> [114,] 1 2 0.9906240 > >>>> [115,] 1 2 0.9865148 > >>>> [116,] 1 2 0.9781846 > >>>> [117,] 1 2 0.9939511 > >>>> [118,] 1 2 0.9931681 > >>>> [119,] 1 2 0.9829519 > >>>> [120,] 1 2 0.9873341 > >>>> [121,] 1 2 0.9916130 > >>>> [122,] 1 2 0.9939273 > >>>> [123,] 1 2 0.9936196 > >>>> [124,] 1 2 0.9930999 > >>>> [125,] 1 2 0.9800620 > >>>> [126,] 1 2 0.9929347 > >>>> [127,] 1 2 0.9820138 > >>>> [128,] 1 2 0.9808614 > >>>> [129,] 1 2 0.9926103 > >>>> [130,] 1 2 0.9938711 > >>>> [131,] 1 2 0.9903987 > >>>> [132,] 1 2 0.9923097 > >>>> [133,] 1 2 0.9921578 > >>>> [134,] 1 2 0.9919558 > >>>> [135,] 1 2 0.9809652 > >>>> [136,] 1 2 0.9799023 > >>>> [137,] 1 2 0.9916220 > >>>> [138,] 1 2 0.9939454 > >>>> [139,] 1 2 0.9935022 > >>>> [140,] 1 2 0.9846059 > >>>> [141,] 1 2 0.9936526 > >>>> [142,] 1 2 0.9937017 > >>>> [143,] 1 2 0.9810402 > >>>> [144,] 1 2 0.9936199 > >>>> [145,] 1 2 0.9897557 > >>>> [146,] 1 2 0.9918058 > >>>> [147,] 1 2 0.9937665 > >>>> [148,] 1 2 0.9882099 > >>>> [149,] 1 2 0.9910776 > >>>> [150,] 1 2 0.9862575 > >>>> [151,] 1 2 0.9911553 > >>>> [152,] 1 2 0.9890393 > >>>> [153,] 1 2 0.9938209 > >>>> [154,] 1 2 0.9901624 > >>>> [155,] 1 2 0.9923515 > >>>> [156,] 1 2 0.9922418 > >>>> [157,] 1 2 0.9889731 > >>>> [158,] 1 2 0.9902939 > >>>> [159,] 1 2 0.9877542 > >>>> [160,] 1 2 0.9910280 > >>>> [161,] 1 2 0.9923092 > >>>> [162,] 1 2 0.9938784 > >>>> [163,] 1 2 0.9914431 > >>>> [164,] 1 2 0.9848184 > >>>> [165,] 1 2 0.9939159 > >>>> [166,] 1 2 0.9939125 > >>>> [167,] 1 2 0.9872706 > >>>> [168,] 1 2 0.9830805 > >>>> [169,] 1 2 0.9913937 > >>>> [170,] 1 2 0.9862925 > >>>> [171,] 1 2 0.9909633 > >>>> [172,] 1 2 0.9788584 > >>>> [173,] 1 2 0.9866989 > >>>> [174,] 1 2 0.9939102 > >>>> [175,] 1 2 0.9853007 > >>>> [176,] 1 2 0.9617883 > >>>> [177,] 1 2 0.9900120 > >>>> [178,] 1 2 0.9918102 > >>>> [179,] 1 2 0.9939489 > >>>> [180,] 1 2 0.9935882 > >>>> [181,] 1 2 0.9917836 > >>>> [182,] 1 2 0.9939170 > >>>> [183,] 1 2 0.9892708 > >>>> [184,] 1 2 0.9924478 > >>>> [185,] 1 2 0.9932287 > >>>> [186,] 1 2 0.9640487 > >>>> [187,] 1 2 0.9150126 > >>>> [188,] 1 2 0.9917589 > >>>> [189,] 1 2 0.9919865 > >>>> [190,] 1 2 0.9937946 > >>>> [191,] 1 2 0.9888295 > >>>> [192,] 1 2 0.9926884 > >>>> [193,] 1 2 0.9909269 > >>>> [194,] 1 2 0.9751339 > >>>> [195,] 1 2 0.9862132 > >>>> [196,] 1 2 0.9841566 > >>>> [197,] 1 2 0.9936557 > >>>> [198,] 1 2 0.9938973 > >>>> [199,] 1 2 0.9934375 > >>>> [200,] 1 2 0.9914201 > >>>> [201,] 1 2 0.9893087 > >>>> [202,] 1 2 0.9915481 > >>>> [203,] 1 2 0.9819092 > >>>> [204,] 1 2 0.9898774 > >>>> [205,] 1 2 0.9926876 > >>>> [206,] 1 2 0.9917091 > >>>> [207,] 1 2 0.9903339 > >>>> [208,] 1 2 0.9764847 > >>>> [209,] 1 2 0.9920887 > >>>> [210,] 1 2 0.9526866 > >>>> [211,] 1 2 0.9938025 > >>>> [212,] 1 2 0.9783714 > >>>> [213,] 1 2 0.9938230 > >>>> [214,] 1 2 0.9880267 > >>>> [215,] 1 2 0.9923108 > >>>> [216,] 1 2 0.9901850 > >>>> [217,] 1 2 0.9938279 > >>>> [218,] 1 2 0.9873388 > >>>> [219,] 1 2 0.9929195 > >>>> [220,] 1 2 0.9934017 > >>>> attr(,"Ordered") > >>>> [1] FALSE > >>>> attr(,"call") > >>>> silhouette.default(x = ifelse(cl1 == 3, 2, 1), dist = dist(x1)^2) > >>>> attr(,"class") > >>>> [1] "silhouette" > >>>> > >>>> ## other examples > >>>>> set.seed(1234) > >>>>> cl.tmp <- rep(2:3, each=5) > >>>>> x.tmp <- c(rep(-1,5), abs(rnorm(5)+3)) > >>>>> silhouette(cl.tmp, dist(x.tmp)) > >>>> cluster neighbor sil_width > >>>> [1,] 2 1 NaN > >>>> [2,] 2 1 NaN > >>>> [3,] 2 1 NaN > >>>> [4,] 2 1 NaN > >>>> [5,] 2 1 NaN > >>>> [6,] 3 2 -0.5736515 > >>>> [7,] 3 2 -0.1557143 > >>>> [8,] 3 2 -0.2922523 > >>>> [9,] 3 2 -0.8340174 > >>>> [10,] 3 2 -0.1511875 > >>>> attr(,"Ordered") > >>>> [1] FALSE > >>>> attr(,"call") > >>>> silhouette.default(x = cl.tmp, dist = dist(x.tmp)) > >>>> attr(,"class") > >>>> [1] "silhouette" > >>>>> silhouette(ifelse(cl.tmp==2,1,2), dist(x.tmp)) > >>>> cluster neighbor sil_width > >>>> [1,] 1 2 1.0000000 > >>>> [2,] 1 2 1.0000000 > >>>> [3,] 1 2 1.0000000 > >>>> [4,] 1 2 1.0000000 > >>>> [5,] 1 2 1.0000000 > >>>> [6,] 2 1 0.4136253 > >>>> [7,] 2 1 0.7038917 > >>>> [8,] 2 1 0.6467668 > >>>> [9,] 2 1 -0.3360695 > >>>> [10,] 2 1 0.7054709 > >>>> attr(,"Ordered") > >>>> [1] FALSE > >>>> attr(,"call") > >>>> silhouette.default(x = ifelse(cl.tmp == 2, 1, 2), dist = dist(x.tmp)) > >>>> attr(,"class") > >>>> [1] "silhouette" > >>>>> silhouette(ifelse(cl.tmp==2,1,3), dist(x.tmp)) > >>>> cluster neighbor sil_width > >>>> [1,] 1 2 NaN > >>>> [2,] 1 2 NaN > >>>> [3,] 1 2 NaN > >>>> [4,] 1 2 NaN > >>>> [5,] 1 2 NaN > >>>> [6,] 3 1 -0.7694686 > >>>> [7,] 3 1 -0.8167313 > >>>> [8,] 3 1 -0.6054665 > >>>> [9,] 3 1 -0.9037412 > >>>> [10,] 3 1 0.1875360 > >>>> attr(,"Ordered") > >>>> [1] FALSE > >>>> attr(,"call") > >>>> silhouette.default(x = ifelse(cl.tmp == 2, 1, 3), dist = dist(x.tmp)) > >>>> attr(,"class") > >>>> [1] "silhouette" > >>>> > >>>> _________________________________________________________________ > >>>> > >>>> It?s free. http://im.live.com/messenger/im/home/?source=TAGHM > >>>> > >>>> <mime-attachment.txt> > >>> > >>> ______________________________________________ > >>> R-help@r-project.org mailing list > >>> https://stat.ethz.ch/mailman/listinfo/r-help > >>> PLEASE do read the posting guide > >>> http://www.R-project.org/posting-guide.html > >>> and provide commented, minimal, self-contained, reproducible code. > >>> > >> > >> -- > >> Brian D. Ripley, rip...@stats.ox.ac.uk > >> Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > >> University of Oxford, Tel: +44 1865 272861 (self) > >> 1 South Parks Road, +44 1865 272866 (PA) > >> Oxford OX1 3TG, UK Fax: +44 1865 272595 > > TS> ______________________________________________ > TS> R-help@r-project.org mailing list > TS> https://stat.ethz.ch/mailman/listinfo/r-help > TS> PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > TS> and provide commented, minimal, self-contained, reproducible code. _________________________________________________________________ Hotmail® goes with you. ial_Mobile1_052009 [[alternative HTML version deleted]]
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
