Status: Done!
Total Time
Max Memory Usage
Domain
MulticlassClassification
Learn time
2s
Train error
0
Predict train time
0s
Test error
0.375
Predict test time
0s
Log file
... (lines omitted) ...
--[AT=1]--- Start Node with 13 exemples, Depth=1
xxx Q with gain(0.0000) error(0.3282) name=[S:35>1.5]
--[AT=1]--- Start Node with 7 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0780) name=[S:12>517.5]
Run weak tree 173
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.8172) name=[S:18>394]
--[AT=1]--- Start Node with 11 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1871) name=[S:13>268.5]
--[AT=1]--- Start Node with 9 exemples, Depth=1
xxx Q with gain(0.0000) error(0.2002) name=[S:43>14.5]
Run weak tree 174
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7524) name=[S:11>120.5]
--[AT=1]--- Start Node with 11 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1850) name=[S:8>49]
--[AT=1]--- Start Node with 9 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1975) name=[S:24>370]
Run weak tree 175
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7598) name=[S:13>860.5]
--[AT=1]--- Start Node with 4 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0000) name=[S:1>470.5]
--[AT=1]--- Start Node with 16 exemples, Depth=1
xxx Q with gain(0.0000) error(0.4762) name=[S:22>577]
Run weak tree 176
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7950) name=[S:30>2.5]
--[AT=1]--- Start Node with 12 exemples, Depth=1
xxx Q with gain(0.0000) error(0.2916) name=[S:25>298.5]
--[AT=1]--- Start Node with 8 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1940) name=[S:1>36.5]
Run weak tree 177
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7975) name=[S:18>394]
--[AT=1]--- Start Node with 11 exemples, Depth=1
xxx Q with gain(0.0000) error(0.2075) name=[S:13>268.5]
--[AT=1]--- Start Node with 9 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1713) name=[S:3>18]
Run weak tree 178
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7755) name=[S:23>806.5]
--[AT=1]--- Start Node with 5 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0000) name=[S:43>53.5]
--[AT=1]--- Start Node with 15 exemples, Depth=1
xxx Q with gain(0.0000) error(0.4857) name=[S:13>860.5]
Run weak tree 179
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.8256) name=[S:2>55.5]
--[AT=1]--- Start Node with 12 exemples, Depth=1
xxx Q with gain(0.0000) error(0.3564) name=[S:30>2.5]
--[AT=1]--- Start Node with 8 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1076) name=[S:27>10]
Run weak tree 180
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7781) name=[S:42>80.5]
--[AT=1]--- Start Node with 4 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0000) name=[S:1>470.5]
--[AT=1]--- Start Node with 16 exemples, Depth=1
xxx Q with gain(0.0000) error(0.4674) name=[S:25>255.5]
Run weak tree 181
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7936) name=[S:11>120.5]
--[AT=1]--- Start Node with 11 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1931) name=[S:8>49]
--[AT=1]--- Start Node with 9 exemples, Depth=1
xxx Q with gain(0.0000) error(0.2057) name=[S:24>370]
Run weak tree 182
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7773) name=[S:13>860.5]
--[AT=1]--- Start Node with 4 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0000) name=[S:1>470.5]
--[AT=1]--- Start Node with 16 exemples, Depth=1
xxx Q with gain(0.0000) error(0.5044) name=[S:20>445.5]
Run weak tree 183
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7901) name=[S:30>2.5]
--[AT=1]--- Start Node with 12 exemples, Depth=1
xxx Q with gain(0.0000) error(0.3068) name=[S:13>218]
--[AT=1]--- Start Node with 8 exemples, Depth=1
xxx Q with gain(0.0000) error(0.2020) name=[S:16>435]
Run weak tree 184
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7852) name=[S:38>0.5]
--[AT=1]--- Start Node with 13 exemples, Depth=1
xxx Q with gain(0.0000) error(0.4513) name=[S:35>1.5]
--[AT=1]--- Start Node with 7 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0639) name=[S:12>517.5]
Run weak tree 185
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7682) name=[S:18>394]
--[AT=1]--- Start Node with 11 exemples, Depth=1
xxx Q with gain(0.0000) error(0.2213) name=[S:13>268.5]
--[AT=1]--- Start Node with 9 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1767) name=[S:9>24]
Run weak tree 186
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7506) name=[S:2>55.5]
--[AT=1]--- Start Node with 12 exemples, Depth=1
xxx Q with gain(0.0000) error(0.2876) name=[S:30>2.5]
--[AT=1]--- Start Node with 8 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0691) name=[S:12>860]
Run weak tree 187
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7689) name=[S:27>33.5]
--[AT=1]--- Start Node with 6 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0399) name=[S:23>473.5]
--[AT=1]--- Start Node with 14 exemples, Depth=1
xxx Q with gain(0.0000) error(0.4916) name=[S:18>394]
Run weak tree 188
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7757) name=[S:7>73.5]
--[AT=1]--- Start Node with 3 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0000) name=[TXT:33]
--[AT=1]--- Start Node with 17 exemples, Depth=1
xxx Q with gain(0.0000) error(0.5824) name=[S:18>394]
Run weak tree 189
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.8202) name=[S:2>55.5]
--[AT=1]--- Start Node with 12 exemples, Depth=1
xxx Q with gain(0.0000) error(0.3996) name=[S:12>172.5]
--[AT=1]--- Start Node with 8 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0679) name=[S:13>860.5]
Run weak tree 190
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7796) name=[S:42>69]
--[AT=1]--- Start Node with 6 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0000) name=[S:13>268.5]
--[AT=1]--- Start Node with 14 exemples, Depth=1
xxx Q with gain(0.0000) error(0.4206) name=[S:2>233.5]
Run weak tree 191
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7723) name=[S:29>2]
--[AT=1]--- Start Node with 17 exemples, Depth=1
xxx Q with gain(0.0000) error(0.5385) name=[S:13>443]
--[AT=1]--- Start Node with 3 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0000) name=[TXT:33]
Run weak tree 192
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.8014) name=[S:27>25.5]
--[AT=1]--- Start Node with 7 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0483) name=[S:13>860.5]
--[AT=1]--- Start Node with 13 exemples, Depth=1
xxx Q with gain(0.0000) error(0.4851) name=[S:11>134]
Run weak tree 193
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.8297) name=[S:9>11]
--[AT=1]--- Start Node with 19 exemples, Depth=1
xxx Q with gain(0.0000) error(0.5675) name=[S:30>2.5]
--[AT=1]--- Start Node with 1 exemples, Depth=1
-> Only one example
Run weak tree 194
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.8049) name=[S:18>394]
--[AT=1]--- Start Node with 11 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1536) name=[S:13>268.5]
--[AT=1]--- Start Node with 9 exemples, Depth=1
xxx Q with gain(0.0000) error(0.2032) name=[S:9>24]
Run weak tree 195
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7783) name=[S:2>55.5]
--[AT=1]--- Start Node with 12 exemples, Depth=1
xxx Q with gain(0.0000) error(0.2812) name=[S:14>231.5]
--[AT=1]--- Start Node with 8 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1023) name=[S:15>145]
Run weak tree 196
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7773) name=[S:27>33.5]
--[AT=1]--- Start Node with 6 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0292) name=[S:23>473.5]
--[AT=1]--- Start Node with 14 exemples, Depth=1
xxx Q with gain(0.0000) error(0.5271) name=[S:22>577]
Run weak tree 197
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.8441) name=[S:2>55.5]
--[AT=1]--- Start Node with 12 exemples, Depth=1
xxx Q with gain(0.0000) error(0.3461) name=[S:45>37]
--[AT=1]--- Start Node with 8 exemples, Depth=1
xxx Q with gain(0.0000) error(0.1325) name=[S:21>164]
Run weak tree 198
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.7862) name=[S:14>231.5]
--[AT=1]--- Start Node with 6 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0000) name=[S:43>30.5]
--[AT=1]--- Start Node with 14 exemples, Depth=1
xxx Q with gain(0.0000) error(0.4325) name=[S:18>394]
Run weak tree 199
--[AT=1]--- Start Node with 20 exemples, Depth=0
xxx Q with gain(0.0000) error(0.8149) name=[S:35>10.5]
--[AT=1]--- Start Node with 3 exemples, Depth=1
xxx Q with gain(0.0000) error(0.0000) name=[S:10>35.5]
--[AT=1]--- Start Node with 17 exemples, Depth=1
xxx Q with gain(0.0000) error(0.5267) name=[S:38>0.5]
run finished
=== END program1: ./run learn ../dataset2/train --- OK [2s]
===== MAIN: predict/evaluate on train data =====
=== START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in
=== END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
Read on stdin: 0 10 20Total features:46
Text features:2
Num features:0
Scored features:44
Load data: 0 0
Warning: Label(1) unknow at line:0
Avoid error computation!
Warning: Label(1) unknow at line:1
Avoid error computation!
Warning: Label(1) unknow at line:2
Avoid error computation!
Warning: Label(1) unknow at line:3
Avoid error computation!
Warning: Label(1) unknow at line:4
Avoid error computation!
Warning: Label(1) unknow at line:5
Avoid error computation!
Warning: Label(1) unknow at line:6
Avoid error computation!
Warning: Label(1) unknow at line:7
Avoid error computation!
Warning: Label(1) unknow at line:8
Avoid error computation!
Warning: Label(1) unknow at line:9
Avoid error computation!
Warning: Label(1) unknow at line:10
Avoid error computation!
Warning: Label(1) unknow at line:11
Avoid error computation!
Warning: Label(1) unknow at line:12
Avoid error computation!
Warning: Label(1) unknow at line:13
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Warning: Label(1) unknow at line:14
Avoid error computation!
Warning: Label(1) unknow at line:15
Avoid error computation!
Warning: Label(1) unknow at line:16
Avoid error computation!
Warning: Label(1) unknow at line:17
Avoid error computation!
Warning: Label(1) unknow at line:18
Avoid error computation!
Warning: Label(1) unknow at line:19
Avoid error computation!
20
0 Go 0 Mo 0 Ko 320 octets
Load round: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200
Example === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [0s]
===== MAIN: predict/evaluate on test data =====
=== START program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in
=== END program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
Read on stdin: 0Total features:46
Text features:2
Num features:0
Scored features:44
Load data: 0 0
Warning: Label(1) unknow at line:0
Avoid error computation!
Warning: Label(1) unknow at line:1
Avoid error computation!
Warning: Label(1) unknow at line:2
Avoid error computation!
Warning: Label(1) unknow at line:3
Avoid error computation!
Warning: Label(1) unknow at line:4
Avoid error computation!
Warning: Label(1) unknow at line:5
Avoid error computation!
Warning: Label(1) unknow at line:6
Avoid error computation!
Warning: Label(1) unknow at line:7
Avoid error computation!
8
0 Go 0 Mo 0 Ko 128 octets
Load round: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200
Example === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [0s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [0s]
real 0m2.053s
user 0m0.956s
sys 0m0.552s
supervised-learning : Main entry for supervised learning for training and testing a program on a dataset.
(learner:Program) bonzaiboost-n200-d2 : 200 turns of AdaBoost.MH over two levels decision trees
(dataset:Dataset) Org study - multiclass :
(stripper:Program[Strip]) multiclass-utils : Validates and inspects a dataset in MulticlassClassification format.
(evaluator:Program[Evaluate]) classification-evaluator : Evaluates predictions of classification datasets (discrete outputs).
doTest:
evaluate:
errorRate: 0.375
numErrors: 3
numExamples: 8
success: true
time: 0
predict:
strip:
doTrain:
evaluate:
errorRate: 0.0
numErrors: 0
numExamples: 20
success: true
time: 0
predict:
strip:
exitCode: 0
learn:
success: true
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