ServerRun 15214
Creatorinternal
Programbonzaiboost-n200-d2
Datasetsynthetic-1000-7500-3-1.00
Task typeMulticlassClassification
Created3y94d ago
DownloadLogin required!
Done! Flag_green
1h16m
773M
MulticlassClassification
0.002
0.297

Log file

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--[AT=1]--- Start Node with 703 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1028) name=[N406:<-1.01604]
Run weak tree 167

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9971) name=[N731:<-19.5952]

--[AT=1]--- Start Node with 738 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0326) name=[N177:<10.4724]

--[AT=1]--- Start Node with 4512 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9591) name=[N503:<-26.4189]
Run weak tree 168

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9973) name=[N448:<-4.60966]

--[AT=1]--- Start Node with 2115 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.2727) name=[N322:<4.31182]

--[AT=1]--- Start Node with 3135 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.7173) name=[N817:<-18.7822]
Run weak tree 169

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9972) name=[N37:<33.6083]

--[AT=1]--- Start Node with 5059 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9711) name=[N309:<28.9131]

--[AT=1]--- Start Node with 191 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0203) name=[N953:<5.80954]
Run weak tree 170

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9972) name=[N670:<18.7069]

--[AT=1]--- Start Node with 4487 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8638) name=[N174:<30.1016]

--[AT=1]--- Start Node with 763 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1251) name=[N183:<17.0467]
Run weak tree 171

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9973) name=[N657:<35.7394]

--[AT=1]--- Start Node with 5132 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9803) name=[N153:<20.1558]

--[AT=1]--- Start Node with 118 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0118) name=[N842:<10.4853]
Run weak tree 172

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9969) name=[N687:<19.2581]

--[AT=1]--- Start Node with 4482 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8790) name=[N997:<3.59354]

--[AT=1]--- Start Node with 768 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1109) name=[N131:<11.4685]
Run weak tree 173

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9971) name=[N713:<-18.3326]

--[AT=1]--- Start Node with 712 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0257) name=[N804:<-0.330199]

--[AT=1]--- Start Node with 4538 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9650) name=[N3:<-14.109]
Run weak tree 174

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9969) name=[N302:<-8.50196]

--[AT=1]--- Start Node with 1363 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1318) name=[N366:<1.45217]

--[AT=1]--- Start Node with 3887 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8578) name=[N62:<-18.1234]
Run weak tree 175

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9969) name=[N458:<4.14318]

--[AT=1]--- Start Node with 2923 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.4823) name=[N642:<5.83469]

--[AT=1]--- Start Node with 2327 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.5077) name=[N122:<-15.9125]
Run weak tree 176

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9967) name=[N783:<-2.38553]

--[AT=1]--- Start Node with 2327 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.3334) name=[N636:<25.6187]

--[AT=1]--- Start Node with 2923 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.6543) name=[N484:<-0.139039]
Run weak tree 177

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9972) name=[N837:<-22.3999]

--[AT=1]--- Start Node with 639 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0211) name=[N505:<-6.55518]

--[AT=1]--- Start Node with 4611 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9700) name=[N421:<2.45863]
Run weak tree 178

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9969) name=[N66:<-13.8792]

--[AT=1]--- Start Node with 1380 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1221) name=[N105:<-2.74777]

--[AT=1]--- Start Node with 3870 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8680) name=[N547:<-16.6823]
Run weak tree 179

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9974) name=[N753:<6.65198]

--[AT=1]--- Start Node with 3517 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.6265) name=[N925:<13.6638]

--[AT=1]--- Start Node with 1733 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.3623) name=[N338:<-16.4154]
Run weak tree 180

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9974) name=[N34:<16.4952]

--[AT=1]--- Start Node with 4363 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8424) name=[N76:<3.96304]

--[AT=1]--- Start Node with 887 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1479) name=[N800:<-9.88476]
Run weak tree 181

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9972) name=[N712:<4.10703]

--[AT=1]--- Start Node with 3033 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.5084) name=[N517:<24.229]

--[AT=1]--- Start Node with 2217 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.4814) name=[N463:<3.82929]
Run weak tree 182

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9974) name=[N528:<8.4578]

--[AT=1]--- Start Node with 3439 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.6223) name=[N532:<9.44348]

--[AT=1]--- Start Node with 1811 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.3666) name=[N424:<2.38558]
Run weak tree 183

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9968) name=[N602:<18.6491]

--[AT=1]--- Start Node with 4490 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8631) name=[N661:<1.38021]

--[AT=1]--- Start Node with 760 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1264) name=[N125:<-9.3804]
Run weak tree 184

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9970) name=[N156:<-1.98551]

--[AT=1]--- Start Node with 2192 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.3007) name=[N103:<-1.30052]

--[AT=1]--- Start Node with 3058 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.6874) name=[N151:<-3.21962]
Run weak tree 185

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9970) name=[N775:<-12.2649]

--[AT=1]--- Start Node with 1310 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1020) name=[N862:<18.5215]

--[AT=1]--- Start Node with 3940 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8878) name=[N351:<-22.0913]
Run weak tree 186

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9974) name=[N332:<-23.3265]

--[AT=1]--- Start Node with 464 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0108) name=[N720:<-25.2402]

--[AT=1]--- Start Node with 4786 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9814) name=[N917:<-30.0114]
Run weak tree 187

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9973) name=[N264:<-13.4077]

--[AT=1]--- Start Node with 1091 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0607) name=[N979:<-5.17698]

--[AT=1]--- Start Node with 4159 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9299) name=[N716:<-26.3629]
Run weak tree 188

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9975) name=[N464:<-9.24385]

--[AT=1]--- Start Node with 1606 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1664) name=[N451:<20.6578]

--[AT=1]--- Start Node with 3644 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8251) name=[N223:<3.06]
Run weak tree 189

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9962) name=[N591:<-7.70215]

--[AT=1]--- Start Node with 1689 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1819) name=[N453:<-0.644004]

--[AT=1]--- Start Node with 3561 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8079) name=[N97:<-7.51659]
Run weak tree 190

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9971) name=[N203:<10.7137]

--[AT=1]--- Start Node with 3836 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.7128) name=[N667:<30.6518]

--[AT=1]--- Start Node with 1414 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.2756) name=[N714:<13.3301]
Run weak tree 191

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9972) name=[N420:<42.2208]

--[AT=1]--- Start Node with 5206 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9919) name=[N716:<0.223409]

--[AT=1]--- Start Node with 44 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0004) name=[N614:<49.0617]
Run weak tree 192

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9963) name=[N760:<-2.85593]

--[AT=1]--- Start Node with 2340 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.3254) name=[N9:<4.88971]

--[AT=1]--- Start Node with 2910 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.6640) name=[N980:<-19.9916]
Run weak tree 193

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9974) name=[N480:<-6.92055]

--[AT=1]--- Start Node with 1958 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.2444) name=[N456:<18.569]

--[AT=1]--- Start Node with 3292 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.7456) name=[N471:<3.55321]
Run weak tree 194

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9968) name=[N666:<7.39473]

--[AT=1]--- Start Node with 3288 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.5649) name=[N903:<25.0578]

--[AT=1]--- Start Node with 1962 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.4242) name=[N148:<-2.42546]
Run weak tree 195

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9973) name=[N79:<9.10696]

--[AT=1]--- Start Node with 3697 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.6836) name=[N679:<20.0941]

--[AT=1]--- Start Node with 1553 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.3032) name=[N869:<16.5328]
Run weak tree 196

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9970) name=[N796:<-14.6379]

--[AT=1]--- Start Node with 1076 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0687) name=[N9:<4.24251]

--[AT=1]--- Start Node with 4174 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9216) name=[N426:<-26.0292]
Run weak tree 197

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9972) name=[N579:<45.5464]

--[AT=1]--- Start Node with 5192 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.9895) name=[N404:<-17.63]

--[AT=1]--- Start Node with 58 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.0031) name=[N308:<21.1868]
Run weak tree 198

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9975) name=[N549:<20.4362]

--[AT=1]--- Start Node with 4585 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.8867) name=[N634:<19.0339]

--[AT=1]--- Start Node with 665 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.1028) name=[N68:<-1.80965]
Run weak tree 199

--[AT=1]--- Start Node with 5250 exemples, Depth=0
	xxx Q with gain(0.0000) error(0.9976) name=[N69:<-5.43143]

--[AT=1]--- Start Node with 1825 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.2013) name=[N516:<19.1259]

--[AT=1]--- Start Node with 3425 exemples, Depth=1
	xxx Q with gain(0.0000) error(0.7889) name=[N190:<-19.0503]
run finished
=== END program1: ./run learn ../dataset2/train --- OK [4336s]

===== 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 [9s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
Read on stdin:     0   10   20   30   40   50   60   70   80   90  100  110  120  130  140  150  160  170  180  190  200  210  220  230  240  250  260  270  280  290  300  310  320  330  340  350  360  370  380  390  400  410  420  430  440  450  460  470  480  490  500  510  520  530  540  550  560  570  580  590  600  610  620  630  640  650  660  670  680  690  700  710  720  730  740  750  760  770  780  790  800  810  820  830  840  850  860  870  880  890  900  910  920  930  940  950  960  970  980  990 1000 1010 1020 1030 1040 1050 1060 1070 1080 1090 1100 1110 1120 1130 1140 1150 1160 1170 1180 1190 1200 1210 1220 1230 1240 1250 1260 1270 1280 1290 1300 1310 1320 1330 1340 1350 1360 1370 1380 1390 1400 1410 1420 1430 1440 1450 1460 1470 1480 1490 1500 1510 1520 1530 1540 1550 1560 1570 1580 1590 1600 1610 1620 1630 1640 1650 1660 1670 1680 1690 1700 1710 1720 1730 1740 1750 1760 1770 1780 1790 1800 1810 1820 1830 1840 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 2110 2120 2130 2140 2150 2160 2170 2180 2190 2200 2210 2220 2230 2240 2250 2260 2270 2280 2290 2300 2310 2320 2330 2340 2350 2360 2370 2380 2390 2400 2410 2420 2430 2440 2450 2460 2470 2480 2490 2500 2510 2520 2530 2540 2550 2560 2570 2580 2590 2600 2610 2620 2630 2640 2650 2660 2670 2680 2690 2700 2710 2720 2730 2740 2750 2760 2770 2780 2790 2800 2810 2820 2830 2840 2850 2860 2870 2880 2890 2900 2910 2920 2930 2940 2950 2960 2970 2980 2990 3000 3010 3020 3030 3040 3050 3060 3070 3080 3090 3100 3110 3120 3130 3140 3150 3160 3170 3180 3190 3200 3210 3220 3230 3240 3250 3260 3270 3280 3290 3300 3310 3320 3330 3340 3350 3360 3370 3380 3390 3400 3410 3420 3430 3440 3450 3460 3470 3480 3490 3500 3510 3520 3530 3540 3550 3560 3570 3580 3590 3600 3610 3620 3630 3640 3650 3660 3670 3680 3690 3700 3710 3720 3730 3740 3750 3760 3770 3780 3790 3800 3810 3820 3830 3840 3850 3860 3870 3880 3890 3900 3910 3920 3930 3940 3950 3960 3970 3980 3990 4000 4010 4020 4030 4040 4050 4060 4070 4080 4090 4100 4110 4120 4130 4140 4150 4160 4170 4180 4190 4200 4210 4220 4230 4240 4250 4260 4270 4280 4290 4300 4310 4320 4330 4340 4350 4360 4370 4380 4390 4400 4410 4420 4430 4440 4450 4460 4470 4480 4490 4500 4510 4520 4530 4540 4550 4560 4570 4580 4590 4600 4610 4620 4630 4640 4650 4660 4670 4680 4690 4700 4710 4720 4730 4740 4750 4760 4770 4780 4790 4800 4810 4820 4830 4840 4850 4860 4870 4880 4890 4900 4910 4920 4930 4940 4950 4960 4970 4980 4990 5000 5010 5020 5030 5040 5050 5060 5070 5080 5090 5100 5110 5120 5130 5140 5150 5160 5170 5180 5190 5200 5210 5220 5230 5240 5250Total features:1000
Text features:0
Num features:1000
Scored features:0
Load data:        0        0     1000     2000     3000     4000     5000     5250

0 Go 42 Mo 84 Ko 0 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      
Error statistics
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
| Label |        HYP |        REF |    Correct |        Err |  Precision |     Recall |  F-Measure |        CER |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
|     1 |       1398 |       5250 |       1398 |       3852 |     100.00 |      26.63 |      42.06 |      73.37 |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
|     2 |       2028 |          0 |          0 |       2028 |       0.00 |     100.00 |       0.00 |  202800.00 |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
|     3 |       1824 |          0 |          0 |       1824 |       0.00 |     100.00 |       0.00 |  182400.00 |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
|   All |       5250 |       5250 |       1398 |       3852 |      26.63 |      26.63 |      26.63 |      73.37 |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [164s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [9s]

===== 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 [4s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
Read on stdin:     0   10   20   30   40   50   60   70   80   90  100  110  120  130  140  150  160  170  180  190  200  210  220  230  240  250  260  270  280  290  300  310  320  330  340  350  360  370  380  390  400  410  420  430  440  450  460  470  480  490  500  510  520  530  540  550  560  570  580  590  600  610  620  630  640  650  660  670  680  690  700  710  720  730  740  750  760  770  780  790  800  810  820  830  840  850  860  870  880  890  900  910  920  930  940  950  960  970  980  990 1000 1010 1020 1030 1040 1050 1060 1070 1080 1090 1100 1110 1120 1130 1140 1150 1160 1170 1180 1190 1200 1210 1220 1230 1240 1250 1260 1270 1280 1290 1300 1310 1320 1330 1340 1350 1360 1370 1380 1390 1400 1410 1420 1430 1440 1450 1460 1470 1480 1490 1500 1510 1520 1530 1540 1550 1560 1570 1580 1590 1600 1610 1620 1630 1640 1650 1660 1670 1680 1690 1700 1710 1720 1730 1740 1750 1760 1770 1780 1790 1800 1810 1820 1830 1840 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 2110 2120 2130 2140 2150 2160 2170 2180 2190 2200 2210 2220 2230 2240 2250Total features:1000
Text features:0
Num features:1000
Scored features:0
Load data:        0        0     1000     2000     2250

0 Go 18 Mo 36 Ko 0 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      
Error statistics
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
| Label |        HYP |        REF |    Correct |        Err |  Precision |     Recall |  F-Measure |        CER |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
|     1 |        534 |       2250 |        534 |       1716 |     100.00 |      23.73 |      38.36 |      76.27 |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
|     2 |        890 |          0 |          0 |        890 |       0.00 |     100.00 |       0.00 |   89000.00 |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
|     3 |        826 |          0 |          0 |        826 |       0.00 |     100.00 |       0.00 |   82600.00 |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
|   All |       2250 |       2250 |        534 |       1716 |      23.73 |      23.73 |      23.73 |      76.27 |
|-------|------------|------------|------------|------------|------------|------------|------------|------------|
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [70s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [4s]


real	76m36.061s
user	49m56.615s
sys	0m18.589s

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Comments:

  • Icon_profile
    ComprarVmx (ComprarVmx)

    Posted at 01/14/2012
    Comprar Vimax
    Saudações. Na verdade, eu fiz algumas navegar na web e dar início a este blog. Vimax Eu firme especial deste blog apresentam-se e é bastante incredible. Vimax I indubitav

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