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List: wekalist
Subject: [Wekalist] =?utf-8?q?V=E1=BB=81=3A_Instant_error_when_use_EM?=
From: Duc Anh <caoboideptrai17 () yahoo ! com ! vn>
Date: 2015-03-30 13:47:09
Message-ID: 1639575533.842874.1427723773266.JavaMail.yahoo () mail ! yahoo ! com
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OK. This is my Java file (ImageRetriveval.java)And this is my trainning file \
(gmm_train1.arff) and the model (gmm_label_1.model).
Và o ngà y 18:40 Thứ Hai, 30 tháng 3 2015, Ralf [via WEKA] \
<ml-node+s8497n34148h90@n7.nabble.com> đã viết:
Could you attach the file
On Mon, Mar 30, 2015 at 12:51 PM, Duc Anh [via WEKA] <[hidden email]> wrote:
This is my EM's result:
=== Run information ===
Scheme:weka.clusterers.EM -I 100 -N 3 -M 1.0E-6 -S 100
Relation: gmm-train
Instances: 61
Attributes: 137
[list of attributes omitted]
Test mode:evaluate on training data
=== Model and evaluation on training set ===
EM
==
Number of clusters: 3
Cluster
Attribute 0 1 2
(0.3) (0.44) (0.26)
==========================================
f1
mean 0.2551 0.226 0.2632
std. dev. 0.099 0.1021 0.0993
f2
mean 0.211 0.2137 0.2114
std. dev. 0.1235 0.1189 0.1126
f3
mean 0.507 0.4911 0.4834
std. dev. 0.1354 0.123 0.1155
f4
mean 0.1733 0.164 0.1758
std. dev. 0.0677 0.0582 0.0865
f5
mean 0.1503 0.1308 0.1227
std. dev. 0.0832 0.0452 0.0586
f6
mean 0.1684 0.1688 0.1543
std. dev. 0.0683 0.0451 0.038
f7
mean 1 1 1
std. dev. 0 0 0
f8
mean 1 1 1
std. dev. 0 0 0
f9
mean 1 1 1
std. dev. 0 0 0
f10
mean 116.3334 118.2963 120.1875
std. dev. 38.6264 43.8582 29.7494
f11
mean 130.7778 129.963 128.6875
std. dev. 55.8615 27.609 14.5418
f12
mean 3.1468 3.3563 3.3615
std. dev. 0.2133 0.1425 0.1154
f13
mean 1.4754 2.0641 1.8069
std. dev. 0.9479 1.3143 0.9863
f14
mean 2117.4446 1435.9631 983.625
std. dev. 518.7518 276.127 177.4859
f15
mean 119.9445 166 189.75
std. dev. 39.2279 35.9465 36.1706
f16
mean 109.6667 145.7778 173.25
std. dev. 27.2906 30.1408 20.6413
f17
mean 135.7222 171.5926 191.125
std. dev. 39.3726 28.1165 29.2956
f18
mean 95.7222 133.037 157.375
std. dev. 37.9295 43.6089 25.2088
f19
mean 98.8889 141.7407 176
std. dev. 51.1608 45.3689 25.1967
f20
mean 106.6111 154.963 190.0625
std. dev. 68.1511 48.3387 43.604
f21
mean 154.2777 217.8148 262.375
std. dev. 87.4101 95.0999 78.4226
f22
mean 122.9444 184.2963 223.625
std. dev. 79.4134 72.636 59.8069
f23
mean 99.5555 147.7778 183.8125
std. dev. 53.5716 45.2224 34.7117
f24
mean 101.6667 136.5926 166.75
std. dev. 55.9236 34.1242 26.0948
f25
mean 125.3889 160.4444 178.9375
std. dev. 51.0579 28.7857 33.6126
f26
mean 92.0556 131.8518 165.0625
std. dev. 31.1599 28.1921 26.3569
f27
mean 104.0556 151.1852 177.5
std. dev. 28.2557 36.3135 25.8215
f28
mean 125.0556 179.3703 219.9375
std. dev. 39.7666 44.1866 37.953
f29
mean 135 185.5926 204.8125
std. dev. 68.5055 72.1615 71.0372
f30
mean 2.8184 2.9294 2.9413
std. dev. 0.1956 0.1038 0.1352
f31
mean 0.3086 0.4401 0.5335
std. dev. 0.1631 0.1574 0.1379
f32
mean 2224.5002 1505.4816 1072.375
std. dev. 393.3403 255.2034 177.6291
f33
mean 140.6111 206.963 252.375
std. dev. 35.7587 30.1987 26.2152
f34
mean 125.2222 188.5555 220.875
std. dev. 30.2849 25.9091 21.5982
f35
mean 140.8889 201.6667 221.625
std. dev. 31.3615 33.5206 19.7796
f36
mean 70.6111 111.963 140.0625
std. dev. 20.0863 21.0792 24.674
f37
mean 70.5555 109.5556 133.75
std. dev. 15.1042 18.6077 15.7063
f38
mean 59.7778 98.2963 124.6875
std. dev. 15.6509 17.2215 18.7107
f39
mean 168.4445 148.4074 163.625
std. dev. 269.027 48.3347 21.3596
f40
mean 49.1111 83.2222 105.625
std. dev. 16.1895 19.7096 20.8593
f41
mean 60.0555 103.037 129.5
std. dev. 19.7131 17.9701 14.7054
f42
mean 77.5555 121.4074 151.8125
std. dev. 21.2138 17.7352 12.9866
f43
mean 116.7222 170.6667 195.5
std. dev. 32.1901 32.0821 26.194
f44
mean 94.5 144.4074 172.25
std. dev. 24.026 17.1664 23.0665
f45
mean 126.8889 188.1111 227
std. dev. 29.8401 23.2177 24.5535
f46
mean 157.3333 231.5556 275.9375
std. dev. 42.868 33.1309 31.2099
f47
mean 161.2222 230.7037 257
std. dev. 68.2573 74.6854 65.8464
f48
mean 2.853 2.9074 2.8688
std. dev. 0.1885 0.1413 0.1243
f49
mean 0.2649 0.3365 0.4219
std. dev. 0.12 0.0722 0.126
f50
mean 2135.4446 1346.4816 866.0625
std. dev. 532.0583 282.7157 189.8633
f51
mean 70.4444 98.037 127.8125
std. dev. 27.1421 18.9844 13.9697
f52
mean 85.8889 121.4074 152.375
std. dev. 28.2369 21.1875 13.6514
f53
mean 135.6667 193.7037 200.6875
std. dev. 32.1541 38.7345 29.5883
f54
mean 90.8333 143.9259 170.8125
std. dev. 32.8689 27.9297 25.1625
f55
mean 116.7778 183.1481 225.625
std. dev. 44.3528 27.3668 30.8826
f56
mean 134.6666 202.5556 259.3125
std. dev. 69.8339 37.3327 31.3423
f57
mean 231.4444 340.963 370.625
std. dev. 104.9408 103.5108 63.5933
f58
mean 144.2777 211.6667 265.9375
std. dev. 95.3186 57.5616 61.3886
f59
mean 132.4444 195.8148 239.6875
std. dev. 62.0163 29.3309 24.6392
f60
mean 118.0556 182.6666 223
std. dev. 41.8867 29.8267 19.9969
f61
mean 140.5556 203.7037 223.75
std. dev. 36.8891 42.644 39.5861
f62
mean 74.9444 107.7407 143.5
std. dev. 32.7795 20.8746 19.6119
f63
mean 77.5556 113.8518 145.5
std. dev. 25.1445 28.2682 15.2439
f64
mean 68.8889 103.8148 128.8125
std. dev. 27.8127 18.9698 15.351
f65
mean 86.1111 94.5185 100.5
std. dev. 56.6695 23.8427 15.2889
f66
mean 2.7067 2.7321 2.729
std. dev. 0.1854 0.1197 0.1023
f67
mean 0.1282 0.1873 0.26
std. dev. 0.0642 0.0636 0.0981
f68
mean 2296.1113 1449.4075 953.375
std. dev. 433.6703 252.9924 177.327
f69
mean 78.3333 130.4815 168.9375
std. dev. 34.817 22.3182 16.6601
f70
mean 99.5555 164.3704 208.4375
std. dev. 31.7931 21.4461 23.569
f71
mean 161.8889 238.4074 262.8125
std. dev. 37.2557 38.8037 26.789
f72
mean 70.6667 117.5926 152.875
std. dev. 31.0107 20.3675 22.0734
f73
mean 91 154.2222 194.75
std. dev. 32.0953 22.7243 25.2004
f74
mean 80.1666 137.5926 178.8125
std. dev. 31.581 25.7197 21.3284
f75
mean 229.1111 270.7778 273.4375
std. dev. 251.593 81.9351 37.653
f76
mean 54.2222 103.1852 126.125
std. dev. 28.5045 34.4395 31.794
f77
mean 82.5 138.7778 177.875
std. dev. 35.9571 31.2852 22.533
f78
mean 99 165.7778 202.375
std. dev. 29.5447 29.417 18.2307
f79
mean 157.2778 230.037 253.1875
std. dev. 43.3203 44.8689 33.4836
f80
mean 72.1111 118.1111 162.875
std. dev. 32.1885 20.5504 24.4179
f81
mean 88.6667 146.7407 190.25
std. dev. 30.2857 17.6459 19.6262
f82
mean 81.2222 144.1111 187.625
std. dev. 33.7385 20.8635 25.0147
f83
mean 102.1667 134.4074 150.25
std. dev. 45.0398 33.4324 27.6349
f84
mean 2.8257 2.9564 2.9398
std. dev. 0.1959 0.1068 0.1221
f85
mean 0.3178 0.4314 0.5855
std. dev. 0.1858 0.1881 0.1663
f86
mean 2433.5558 1548.7779 1062.125
std. dev. 408.3429 274.4095 213.6817
f87
mean 101.1111 164.8148 203.125
std. dev. 37.4283 27.7809 25.0072
f88
mean 102.2222 166.8889 206.5
std. dev. 31.9958 26.1241 20.0624
f89
mean 129.2222 204.6666 227
std. dev. 37.7721 31.9224 21.9545
f90
mean 68.4444 119.8148 160.8125
std. dev. 29.9225 18.1272 17.8263
f91
mean 67.6111 126.0741 159.9375
std. dev. 30.3116 17.0878 21.2205
f92
mean 56.5 114.3704 149.75
std. dev. 25.5805 15.2125 18.5927
f93
mean 178 217 199.4375
std. dev. 131.8459 130.9277 28.6508
f94
mean 57.3333 97.5926 137.6875
std. dev. 32.5866 18.7444 27.1079
f95
mean 60.2222 118.4444 154.875
std. dev. 29.1406 13.7581 19.4
f96
mean 71.0555 137.8889 170
std. dev. 27.5972 19.7059 15.6645
f97
mean 113.6667 188.2963 220.375
std. dev. 33.9133 36.3255 28.1555
f98
mean 84.0555 138.8148 178.25
std. dev. 32.7914 20.2705 21.1852
f99
mean 97.8889 164.5555 205.1875
std. dev. 30.7551 22.4489 24.8048
f100
mean 114.7222 179.7778 217.5625
std. dev. 41.2133 32.4052 40.8946
f101
mean 108.3889 156.2222 191.375
std. dev. 44.76 42.9292 41.4033
f102
mean 2.836 2.8669 2.8987
std. dev. 0.1824 0.1836 0.1367
f103
mean 0.2333 0.3282 0.4333
std. dev. 0.1045 0.0832 0.171
f104
mean 2506.8334 1840.0372 1148.9375
std. dev. 516.2655 298.7821 297.908
f105
mean 49.6111 89.2222 127.3125
std. dev. 31.0182 29.0075 29.4952
f106
mean 63.1111 103.9629 152.4375
std. dev. 29.318 28.8746 36.7031
f107
mean 119.9445 165.5926 207.125
std. dev. 45.2873 34.6648 38.3925
f108
mean 65.2222 111.5555 160.625
std. dev. 29.4384 21.6527 22.2679
f109
mean 90.3889 130.6667 181.625
std. dev. 42.1032 23.9088 24.101
f110
mean 89.3333 132.8148 187.875
std. dev. 47.0484 29.1472 26.2842
f111
mean 147.0555 208.4445 262.25
std. dev. 70.7024 66.754 48.8998
f112
mean 93 130.4445 191.375
std. dev. 57.036 31.6723 42.6964
f113
mean 86.3889 133.4074 189.5
std. dev. 46.7869 23.7553 27.1224
f114
mean 90.1111 131.6296 188.8125
std. dev. 37.409 21.9581 28.9811
f115
mean 120.5 174.5185 221.9375
std. dev. 44.3061 36.2965 44.9325
f116
mean 61.9445 94.1852 144.4375
std. dev. 32.5738 25.5561 30.6145
f117
mean 60.4444 101.7778 147
std. dev. 31.6442 30.5194 33.5075
f118
mean 53.3889 93.4074 133.75
std. dev. 31.6546 26.0616 35.9418
f119
mean 146.7222 202.3333 199
std. dev. 70.1489 123.8153 65.8986
f120
mean 2.7674 2.8048 2.814
std. dev. 0.1784 0.1747 0.0873
f121
mean 0.1119 0.1728 0.2673
std. dev. 0.0721 0.069 0.1261
f122
mean 2752.2779 1938.889 1210.4375
std. dev. 473.1222 319.4962 325.2841
f123
mean 47.0556 90.5555 137.6875
std. dev. 37.2715 30.6489 25.2876
f124
mean 55.2778 110.6667 168.25
std. dev. 33.7981 30.3998 37.5591
f125
mean 134.5 191.5555 250.8125
std. dev. 42.937 46.9857 37.4854
f126
mean 51.6111 93.037 145.375
std. dev. 36.8377 24.832 31.849
f127
mean 58 111.8148 167.25
std. dev. 39.3023 18.3929 33.186
f128
mean 50.7222 100.8148 154.5
std. dev. 35.6165 19.6394 30.749
f129
mean 137.7222 218.6667 239.4375
std. dev. 70.3379 94.1681 43.6319
f130
mean 42.1111 78.7407 120.25
std. dev. 34.4801 24.6796 31.7342
f131
mean 53.3889 104.0741 151.5
std. dev. 35.9601 20.5191 25.0475
f132
mean 56.6111 121.2963 175.9375
std. dev. 35.991 26.1786 30.5869
f133
mean 132.7778 188.8889 235.375
std. dev. 45.1486 46.6503 38.0836
f134
mean 52.3889 91.2593 149.375
std. dev. 38.2392 27.235 35.3622
f135
mean 51.1111 105.6667 161.3125
std. dev. 34.2489 28.1412 32.3317
f136
mean 50.5 99.1481 157.375
std. dev. 35.2897 32.1717 35.1281
f137
mean 117.9444 198.9259 219.125
std. dev. 57.9276 102.0715 65.3604
Time taken to build model (full training data) : 0.31 seconds
=== Model and evaluation on training set ===
Clustered Instances
0 18 ( 30%)
1 27 ( 44%)
2 16 ( 26%)
Log likelihood: -522.78877
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ImageRetrieval.java (36K) \
<http://weka.8497.n7.nabble.com/attachment/34149/0/ImageRetrieval.java> \
gmm_label_1.model (86K) \
<http://weka.8497.n7.nabble.com/attachment/34149/1/gmm_label_1.model> gmm-train1.arff \
(65K) <http://weka.8497.n7.nabble.com/attachment/34149/2/gmm-train1.arff>
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[Attachment #5 (text/html)]
<div style="color:#000; background-color:#fff; font-family:HelveticaNeue, Helvetica \
Neue, Helvetica, Arial, Lucida Grande, sans-serif;font-size:16px"><div dir="ltr" \
id="yui_3_16_0_1_1427722870740_7025"><span id="yui_3_16_0_1_1427722870740_7035">OK. \
This is my Java file (ImageRetriveval.java)</span></div><div \
id="yui_3_16_0_1_1427722870740_8970" dir="ltr"><span \
id="yui_3_16_0_1_1427722870740_7035">And this is my trainning file (gmm_train1.arff) \
and the model (gmm_label_1.model).</span></div> <br><div \
class="qtdSeparateBR"><br><br></div><div style="display: block;" \
class="yahoo_quoted"> <div style="font-family: HelveticaNeue, Helvetica Neue, \
Helvetica, Arial, Lucida Grande, sans-serif; font-size: 16px;"> <div \
style="font-family: HelveticaNeue, Helvetica Neue, Helvetica, Arial, Lucida Grande, \
sans-serif; font-size: 16px;"> <div dir="ltr"> <font size="2" face="Arial"> Và o ngà \
y 18:40 Thứ Hai, 30 tháng 3 2015, Ralf [via WEKA] <<a \
href="/user/SendEmail.jtp?type=node&node=34149&i=0" target="_top" rel="nofollow" \
link="external">[hidden email]</a>> đã viết:<br> </font> </div> <br><br> <div \
class="y_msg_container"><div id="yiv4626304752">
<div dir="ltr">Could you attach the file<br></div><div \
class="yiv4626304752gmail_extra"><br><div class="yiv4626304752gmail_quote">On Mon, \
Mar 30, 2015 at 12:51 PM, Duc Anh [via WEKA] <span dir="ltr"><<a href="" \
rel="nofollow" target="_top" link="external">[hidden email]</a>></span> \
wrote:<br><blockquote style='border-left:2px solid #CCCCCC;padding:0 1em' \
style="border-left:2px solid #CCCCCC;padding:0 1em;" \
class="yiv4626304752gmail_quote">
This is my EM's result:
<br>=== Run information ===
<br><br>Scheme:weka.clusterers.EM -I 100 -N 3 -M 1.0E-6 -S 100
<br>Relation: gmm-train
<br>Instances: 61
<br>Attributes: 137
<br>[list of attributes omitted]
<br>Test mode:evaluate on training data
<br><br>=== Model and evaluation on training set ===
<br><br><br>EM
<br>==
<br><br>Number of clusters: 3
<br><br><br> Cluster
<br>Attribute 0 1 \
2 <br> \
(0.3) (0.44) (0.26) \
<br>========================================== <br>f1
<br> mean 0.2551 0.226 \
0.2632 <br> std. dev. 0.099 0.1021 \
0.0993 <br><br>f2
<br> mean 0.211 0.2137 \
0.2114 <br> std. dev. 0.1235 0.1189 \
0.1126 <br><br>f3
<br> mean 0.507 0.4911 \
0.4834 <br> std. dev. 0.1354 0.123 \
0.1155 <br><br>f4
<br> mean 0.1733 0.164 \
0.1758 <br> std. dev. 0.0677 0.0582 \
0.0865 <br><br>f5
<br> mean 0.1503 0.1308 \
0.1227 <br> std. dev. 0.0832 0.0452 \
0.0586 <br><br>f6
<br> mean 0.1684 0.1688 \
0.1543 <br> std. dev. 0.0683 0.0451 \
0.038 <br><br>f7
<br> mean 1 \
1 1 <br> std. dev. \
0 0 0 \
<br><br>f8 <br> mean 1 \
1 1 <br> std. dev. \
0 0 \
0 <br><br>f9
<br> mean 1 \
1 1 <br> std. dev. \
0 0 0 \
<br><br>f10 <br> mean 116.3334 118.2963 \
120.1875 <br> std. dev. 38.6264 43.8582 \
29.7494 <br><br>f11
<br> mean 130.7778 129.963 128.6875
<br> std. dev. 55.8615 27.609 14.5418
<br><br>f12
<br> mean 3.1468 3.3563 \
3.3615 <br> std. dev. 0.2133 0.1425 \
0.1154 <br><br>f13
<br> mean 1.4754 2.0641 \
1.8069 <br> std. dev. 0.9479 1.3143 \
0.9863 <br><br>f14
<br> mean 2117.4446 1435.9631 983.625
<br> std. dev. 518.7518 276.127 177.4859
<br><br>f15
<br> mean 119.9445 166 \
189.75 <br> std. dev. 39.2279 35.9465 36.1706
<br><br>f16
<br> mean 109.6667 145.7778 \
173.25 <br> std. dev. 27.2906 30.1408 20.6413
<br><br>f17
<br> mean 135.7222 171.5926 191.125
<br> std. dev. 39.3726 28.1165 29.2956
<br><br>f18
<br> mean 95.7222 133.037 157.375
<br> std. dev. 37.9295 43.6089 25.2088
<br><br>f19
<br> mean 98.8889 141.7407 \
176 <br> std. dev. 51.1608 45.3689 25.1967
<br><br>f20
<br> mean 106.6111 154.963 190.0625
<br> std. dev. 68.1511 48.3387 43.604
<br><br>f21
<br> mean 154.2777 217.8148 262.375
<br> std. dev. 87.4101 95.0999 78.4226
<br><br>f22
<br> mean 122.9444 184.2963 223.625
<br> std. dev. 79.4134 72.636 59.8069
<br><br>f23
<br> mean 99.5555 147.7778 183.8125
<br> std. dev. 53.5716 45.2224 34.7117
<br><br>f24
<br> mean 101.6667 136.5926 \
166.75 <br> std. dev. 55.9236 34.1242 26.0948
<br><br>f25
<br> mean 125.3889 160.4444 178.9375
<br> std. dev. 51.0579 28.7857 33.6126
<br><br>f26
<br> mean 92.0556 131.8518 165.0625
<br> std. dev. 31.1599 28.1921 26.3569
<br><br>f27
<br> mean 104.0556 151.1852 \
177.5 <br> std. dev. 28.2557 36.3135 25.8215
<br><br>f28
<br> mean 125.0556 179.3703 219.9375
<br> std. dev. 39.7666 44.1866 37.953
<br><br>f29
<br> mean 135 185.5926 \
204.8125 <br> std. dev. 68.5055 72.1615 \
71.0372 <br><br>f30
<br> mean 2.8184 2.9294 \
2.9413 <br> std. dev. 0.1956 0.1038 \
0.1352 <br><br>f31
<br> mean 0.3086 0.4401 \
0.5335 <br> std. dev. 0.1631 0.1574 \
0.1379 <br><br>f32
<br> mean 2224.5002 1505.4816 1072.375
<br> std. dev. 393.3403 255.2034 177.6291
<br><br>f33
<br> mean 140.6111 206.963 252.375
<br> std. dev. 35.7587 30.1987 26.2152
<br><br>f34
<br> mean 125.2222 188.5555 220.875
<br> std. dev. 30.2849 25.9091 21.5982
<br><br>f35
<br> mean 140.8889 201.6667 221.625
<br> std. dev. 31.3615 33.5206 19.7796
<br><br>f36
<br> mean 70.6111 111.963 140.0625
<br> std. dev. 20.0863 21.0792 24.674
<br><br>f37
<br> mean 70.5555 109.5556 \
133.75 <br> std. dev. 15.1042 18.6077 15.7063
<br><br>f38
<br> mean 59.7778 98.2963 124.6875
<br> std. dev. 15.6509 17.2215 18.7107
<br><br>f39
<br> mean 168.4445 148.4074 163.625
<br> std. dev. 269.027 48.3347 21.3596
<br><br>f40
<br> mean 49.1111 83.2222 105.625
<br> std. dev. 16.1895 19.7096 20.8593
<br><br>f41
<br> mean 60.0555 103.037 \
129.5 <br> std. dev. 19.7131 17.9701 14.7054
<br><br>f42
<br> mean 77.5555 121.4074 151.8125
<br> std. dev. 21.2138 17.7352 12.9866
<br><br>f43
<br> mean 116.7222 170.6667 \
195.5 <br> std. dev. 32.1901 32.0821 26.194
<br><br>f44
<br> mean 94.5 144.4074 \
172.25 <br> std. dev. 24.026 17.1664 23.0665
<br><br>f45
<br> mean 126.8889 188.1111 \
227 <br> std. dev. 29.8401 23.2177 24.5535
<br><br>f46
<br> mean 157.3333 231.5556 275.9375
<br> std. dev. 42.868 33.1309 31.2099
<br><br>f47
<br> mean 161.2222 230.7037 \
257 <br> std. dev. 68.2573 74.6854 65.8464
<br><br>f48
<br> mean 2.853 2.9074 \
2.8688 <br> std. dev. 0.1885 0.1413 \
0.1243 <br><br>f49
<br> mean 0.2649 0.3365 \
0.4219 <br> std. dev. 0.12 0.0722 \
0.126 <br><br>f50
<br> mean 2135.4446 1346.4816 866.0625
<br> std. dev. 532.0583 282.7157 189.8633
<br><br>f51
<br> mean 70.4444 98.037 \
127.8125 <br> std. dev. 27.1421 18.9844 \
13.9697 <br><br>f52
<br> mean 85.8889 121.4074 152.375
<br> std. dev. 28.2369 21.1875 13.6514
<br><br>f53
<br> mean 135.6667 193.7037 200.6875
<br> std. dev. 32.1541 38.7345 29.5883
<br><br>f54
<br> mean 90.8333 143.9259 170.8125
<br> std. dev. 32.8689 27.9297 25.1625
<br><br>f55
<br> mean 116.7778 183.1481 225.625
<br> std. dev. 44.3528 27.3668 30.8826
<br><br>f56
<br> mean 134.6666 202.5556 259.3125
<br> std. dev. 69.8339 37.3327 31.3423
<br><br>f57
<br> mean 231.4444 340.963 370.625
<br> std. dev. 104.9408 103.5108 63.5933
<br><br>f58
<br> mean 144.2777 211.6667 265.9375
<br> std. dev. 95.3186 57.5616 61.3886
<br><br>f59
<br> mean 132.4444 195.8148 239.6875
<br> std. dev. 62.0163 29.3309 24.6392
<br><br>f60
<br> mean 118.0556 182.6666 \
223 <br> std. dev. 41.8867 29.8267 19.9969
<br><br>f61
<br> mean 140.5556 203.7037 \
223.75 <br> std. dev. 36.8891 42.644 \
39.5861 <br><br>f62
<br> mean 74.9444 107.7407 \
143.5 <br> std. dev. 32.7795 20.8746 19.6119
<br><br>f63
<br> mean 77.5556 113.8518 \
145.5 <br> std. dev. 25.1445 28.2682 15.2439
<br><br>f64
<br> mean 68.8889 103.8148 128.8125
<br> std. dev. 27.8127 18.9698 15.351
<br><br>f65
<br> mean 86.1111 94.5185 \
100.5 <br> std. dev. 56.6695 23.8427 15.2889
<br><br>f66
<br> mean 2.7067 2.7321 \
2.729 <br> std. dev. 0.1854 0.1197 \
0.1023 <br><br>f67
<br> mean 0.1282 0.1873 \
0.26 <br> std. dev. 0.0642 0.0636 \
0.0981 <br><br>f68
<br> mean 2296.1113 1449.4075 953.375
<br> std. dev. 433.6703 252.9924 177.327
<br><br>f69
<br> mean 78.3333 130.4815 168.9375
<br> std. dev. 34.817 22.3182 16.6601
<br><br>f70
<br> mean 99.5555 164.3704 208.4375
<br> std. dev. 31.7931 21.4461 23.569
<br><br>f71
<br> mean 161.8889 238.4074 262.8125
<br> std. dev. 37.2557 38.8037 26.789
<br><br>f72
<br> mean 70.6667 117.5926 152.875
<br> std. dev. 31.0107 20.3675 22.0734
<br><br>f73
<br> mean 91 154.2222 \
194.75 <br> std. dev. 32.0953 22.7243 \
25.2004 <br><br>f74
<br> mean 80.1666 137.5926 178.8125
<br> std. dev. 31.581 25.7197 21.3284
<br><br>f75
<br> mean 229.1111 270.7778 273.4375
<br> std. dev. 251.593 81.9351 37.653
<br><br>f76
<br> mean 54.2222 103.1852 126.125
<br> std. dev. 28.5045 34.4395 31.794
<br><br>f77
<br> mean 82.5 138.7778 \
177.875 <br> std. dev. 35.9571 31.2852 22.533
<br><br>f78
<br> mean 99 165.7778 \
202.375 <br> std. dev. 29.5447 29.417 \
18.2307 <br><br>f79
<br> mean 157.2778 230.037 253.1875
<br> std. dev. 43.3203 44.8689 33.4836
<br><br>f80
<br> mean 72.1111 118.1111 162.875
<br> std. dev. 32.1885 20.5504 24.4179
<br><br>f81
<br> mean 88.6667 146.7407 \
190.25 <br> std. dev. 30.2857 17.6459 19.6262
<br><br>f82
<br> mean 81.2222 144.1111 187.625
<br> std. dev. 33.7385 20.8635 25.0147
<br><br>f83
<br> mean 102.1667 134.4074 \
150.25 <br> std. dev. 45.0398 33.4324 27.6349
<br><br>f84
<br> mean 2.8257 2.9564 \
2.9398 <br> std. dev. 0.1959 0.1068 \
0.1221 <br><br>f85
<br> mean 0.3178 0.4314 \
0.5855 <br> std. dev. 0.1858 0.1881 \
0.1663 <br><br>f86
<br> mean 2433.5558 1548.7779 1062.125
<br> std. dev. 408.3429 274.4095 213.6817
<br><br>f87
<br> mean 101.1111 164.8148 203.125
<br> std. dev. 37.4283 27.7809 25.0072
<br><br>f88
<br> mean 102.2222 166.8889 \
206.5 <br> std. dev. 31.9958 26.1241 20.0624
<br><br>f89
<br> mean 129.2222 204.6666 \
227 <br> std. dev. 37.7721 31.9224 21.9545
<br><br>f90
<br> mean 68.4444 119.8148 160.8125
<br> std. dev. 29.9225 18.1272 17.8263
<br><br>f91
<br> mean 67.6111 126.0741 159.9375
<br> std. dev. 30.3116 17.0878 21.2205
<br><br>f92
<br> mean 56.5 114.3704 \
149.75 <br> std. dev. 25.5805 15.2125 18.5927
<br><br>f93
<br> mean 178 \
217 199.4375 <br> std. dev. 131.8459 130.9277 28.6508
<br><br>f94
<br> mean 57.3333 97.5926 137.6875
<br> std. dev. 32.5866 18.7444 27.1079
<br><br>f95
<br> mean 60.2222 118.4444 154.875
<br> std. dev. 29.1406 13.7581 19.4
<br><br>f96
<br> mean 71.0555 137.8889 \
170 <br> std. dev. 27.5972 19.7059 15.6645
<br><br>f97
<br> mean 113.6667 188.2963 220.375
<br> std. dev. 33.9133 36.3255 28.1555
<br><br>f98
<br> mean 84.0555 138.8148 \
178.25 <br> std. dev. 32.7914 20.2705 21.1852
<br><br>f99
<br> mean 97.8889 164.5555 205.1875
<br> std. dev. 30.7551 22.4489 24.8048
<br><br>f100
<br> mean 114.7222 179.7778 217.5625
<br> std. dev. 41.2133 32.4052 40.8946
<br><br>f101
<br> mean 108.3889 156.2222 191.375
<br> std. dev. 44.76 42.9292 41.4033
<br><br>f102
<br> mean 2.836 2.8669 \
2.8987 <br> std. dev. 0.1824 0.1836 \
0.1367 <br><br>f103
<br> mean 0.2333 0.3282 \
0.4333 <br> std. dev. 0.1045 0.0832 \
0.171 <br><br>f104
<br> mean 2506.8334 1840.0372 1148.9375
<br> std. dev. 516.2655 298.7821 297.908
<br><br>f105
<br> mean 49.6111 89.2222 127.3125
<br> std. dev. 31.0182 29.0075 29.4952
<br><br>f106
<br> mean 63.1111 103.9629 152.4375
<br> std. dev. 29.318 28.8746 36.7031
<br><br>f107
<br> mean 119.9445 165.5926 207.125
<br> std. dev. 45.2873 34.6648 38.3925
<br><br>f108
<br> mean 65.2222 111.5555 160.625
<br> std. dev. 29.4384 21.6527 22.2679
<br><br>f109
<br> mean 90.3889 130.6667 181.625
<br> std. dev. 42.1032 23.9088 24.101
<br><br>f110
<br> mean 89.3333 132.8148 187.875
<br> std. dev. 47.0484 29.1472 26.2842
<br><br>f111
<br> mean 147.0555 208.4445 \
262.25 <br> std. dev. 70.7024 66.754 \
48.8998 <br><br>f112
<br> mean 93 130.4445 \
191.375 <br> std. dev. 57.036 31.6723 \
42.6964 <br><br>f113
<br> mean 86.3889 133.4074 \
189.5 <br> std. dev. 46.7869 23.7553 27.1224
<br><br>f114
<br> mean 90.1111 131.6296 188.8125
<br> std. dev. 37.409 21.9581 28.9811
<br><br>f115
<br> mean 120.5 174.5185 \
221.9375 <br> std. dev. 44.3061 36.2965 \
44.9325 <br><br>f116
<br> mean 61.9445 94.1852 144.4375
<br> std. dev. 32.5738 25.5561 30.6145
<br><br>f117
<br> mean 60.4444 101.7778 \
147 <br> std. dev. 31.6442 30.5194 33.5075
<br><br>f118
<br> mean 53.3889 93.4074 \
133.75 <br> std. dev. 31.6546 26.0616 35.9418
<br><br>f119
<br> mean 146.7222 202.3333 \
199 <br> std. dev. 70.1489 123.8153 65.8986
<br><br>f120
<br> mean 2.7674 2.8048 \
2.814 <br> std. dev. 0.1784 0.1747 \
0.0873 <br><br>f121
<br> mean 0.1119 0.1728 \
0.2673 <br> std. dev. 0.0721 0.069 \
0.1261 <br><br>f122
<br> mean 2752.2779 1938.889 1210.4375
<br> std. dev. 473.1222 319.4962 325.2841
<br><br>f123
<br> mean 47.0556 90.5555 137.6875
<br> std. dev. 37.2715 30.6489 25.2876
<br><br>f124
<br> mean 55.2778 110.6667 \
168.25 <br> std. dev. 33.7981 30.3998 37.5591
<br><br>f125
<br> mean 134.5 191.5555 \
250.8125 <br> std. dev. 42.937 46.9857 \
37.4854 <br><br>f126
<br> mean 51.6111 93.037 \
145.375 <br> std. dev. 36.8377 24.832 \
31.849 <br><br>f127
<br> mean 58 111.8148 \
167.25 <br> std. dev. 39.3023 18.3929 \
33.186 <br><br>f128
<br> mean 50.7222 100.8148 \
154.5 <br> std. dev. 35.6165 19.6394 30.749
<br><br>f129
<br> mean 137.7222 218.6667 239.4375
<br> std. dev. 70.3379 94.1681 43.6319
<br><br>f130
<br> mean 42.1111 78.7407 \
120.25 <br> std. dev. 34.4801 24.6796 31.7342
<br><br>f131
<br> mean 53.3889 104.0741 \
151.5 <br> std. dev. 35.9601 20.5191 25.0475
<br><br>f132
<br> mean 56.6111 121.2963 175.9375
<br> std. dev. 35.991 26.1786 30.5869
<br><br>f133
<br> mean 132.7778 188.8889 235.375
<br> std. dev. 45.1486 46.6503 38.0836
<br><br>f134
<br> mean 52.3889 91.2593 149.375
<br> std. dev. 38.2392 27.235 35.3622
<br><br>f135
<br> mean 51.1111 105.6667 161.3125
<br> std. dev. 34.2489 28.1412 32.3317
<br><br>f136
<br> mean 50.5 99.1481 \
157.375 <br> std. dev. 35.2897 32.1717 35.1281
<br><br>f137
<br> mean 117.9444 198.9259 219.125
<br> std. dev. 57.9276 102.0715 65.3604
<br><br><br><br>Time taken to build model (full training data) : 0.31 seconds
<br><br>=== Model and evaluation on training set ===
<br><br>Clustered Instances
<br><br>0 18 ( 30%)
<br>1 27 ( 44%)
<br>2 16 ( 26%)
<br><br><br>Log likelihood: -522.78877
<br>
<br>
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