ServerRun 30475
CreatorVeovis
Programsvmlight-linear
Datasetrepere
Task typeBinaryClassification
Created3y215d ago
DownloadLogin required!
Done! Flag_green
1m2s
42M
BinaryClassification
51s
0.099
4s
0.094
3s

Log file

===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
Scanning examples...done
Reading examples into memory...100..200..300..400..500..600..700..800..900..1000..1100..1200..1300..1400..1500..1600..1700..1800..1900..2000..2100..2200..2300..2400..2500..2600..2700..2800..2900..3000..3100..3200..3300..3400..3500..3600..3700..3800..3900..4000..4100..4200..4300..4400..4500..4600..4700..4800..4900..5000..5100..5200..5300..5400..5500..5600..5700..5800..5900..6000..6100..6200..6300..6400..6500..6600..6700..6800..6900..7000..7100..7200..7300..7400..7500..7600..7700..7800..7900..8000..8100..8200..8300..8400..8500..8600..8700..8800..8900..9000..9100..9200..9300..9400..9500..9600..9700..9800..9900..10000..10100..10200..10300..10400..10500..10600..10700..10800..10900..11000..11100..11200..11300..11400..11500..11600..11700..11800..11900..12000..12100..12200..12300..12400..12500..12600..12700..12800..12900..13000..13100..13200..13300..13400..13500..13600..13700..13800..13900..14000..14100..14200..14300..14400..14500..14600..14700..14800..14900..15000..15100..15200..15300..15400..15500..15600..15700..15800..15900..16000..16100..16200..16300..16400..16500..16600..16700..16800..16900..17000..17100..17200..17300..17400..17500..17600..17700..17800..17900..18000..18100..18200..18300..18400..18500..18600..18700..18800..18900..19000..19100..19200..19300..19400..19500..19600..19700..19800..19900..20000..20100..20200..20300..20400..20500..20600..20700..20800..20900..21000..21100..21200..21300..21400..21500..21600..21700..21800..21900..22000..22100..22200..22300..22400..22500..22600..22700..22800..22900..23000..23100..23200..23300..23400..23500..23600..23700..23800..23900..24000..24100..24200..24300..24400..24500..24600..24700..24800..24900..25000..25100..25200..25300..25400..25500..25600..25700..25800..25900..26000..26100..26200..26300..26400..26500..26600..26700..26800..26900..27000..27100..27200..27300..27400..27500..27600..27700..27800..27900..28000..28100..28200..28300..28400..28500..28600..28700..28800..28900..29000..29100..29200..29300..29400..29500..29600..29700..29800..29900..30000..30100..30200..30300..30400..30500..30600..30700..30800..30900..31000..31100..31200..31300..31400..31500..31600..31700..31800..31900..32000..32100..32200..32300..32400..32500..32600..32700..32800..32900..33000..33100..33200..33300..33400..33500..33600..33700..33800..33900..34000..34100..34200..34300..34400..34500..34600..34700..34800..34900..35000..35100..35200..35300..35400..35500..35600..35700..35800..35900..36000..36100..36200..36300..36400..36500..36600..36700..36800..36900..37000..37100..37200..37300..37400..37500..37600..37700..37800..37900..38000..38100..38200..38300..38400..38500..38600..38700..38800..38900..39000..39100..39200..39300..39400..39500..39600..39700..39800..39900..40000..40100..40200..40300..40400..40500..40600..40700..40800..40900..41000..41100..41200..41300..41400..41500..OK. (41523 examples read)
Setting default regularization parameter C=0.0125
Optimizing..............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................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(7194 iterations)
Optimization finished (4107 misclassified, maxdiff=0.00098).
Runtime in cpu-seconds: 47.04
Number of SV: 8355 (including 8263 at upper bound)
L1 loss: loss=8212.98956
Norm of weight vector: |w|=0.99943
Norm of longest example vector: |x|=15.35686
Estimated VCdim of classifier: VCdim<=183.13637
Computing XiAlpha-estimates...done
Runtime for XiAlpha-estimates in cpu-seconds: 0.01
XiAlpha-estimate of the error: error<=19.99% (rho=1.00,depth=0)
XiAlpha-estimate of the recall: recall=>72.88% (rho=1.00,depth=0)
XiAlpha-estimate of the precision: precision=>72.90% (rho=1.00,depth=0)
Number of kernel evaluations: 835873
Writing model file...done
=== END program1: ./run learn ../dataset2/train --- OK [51s]

===== 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 [1s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
Reading model...OK. (8355 support vectors read)
Classifying test examples..100..200..300..400..500..600..700..800..900..1000..1100..1200..1300..1400..1500..1600..1700..1800..1900..2000..2100..2200..2300..2400..2500..2600..2700..2800..2900..3000..3100..3200..3300..3400..3500..3600..3700..3800..3900..4000..4100..4200..4300..4400..4500..4600..4700..4800..4900..5000..5100..5200..5300..5400..5500..5600..5700..5800..5900..6000..6100..6200..6300..6400..6500..6600..6700..6800..6900..7000..7100..7200..7300..7400..7500..7600..7700..7800..7900..8000..8100..8200..8300..8400..8500..8600..8700..8800..8900..9000..9100..9200..9300..9400..9500..9600..9700..9800..9900..10000..10100..10200..10300..10400..10500..10600..10700..10800..10900..11000..11100..11200..11300..11400..11500..11600..11700..11800..11900..12000..12100..12200..12300..12400..12500..12600..12700..12800..12900..13000..13100..13200..13300..13400..13500..13600..13700..13800..13900..14000..14100..14200..14300..14400..14500..14600..14700..14800..14900..15000..15100..15200..15300..15400..15500..15600..15700..15800..15900..16000..16100..16200..16300..16400..16500..16600..16700..16800..16900..17000..17100..17200..17300..17400..17500..17600..17700..17800..17900..18000..18100..18200..18300..18400..18500..18600..18700..18800..18900..19000..19100..19200..19300..19400..19500..19600..19700..19800..19900..20000..20100..20200..20300..20400..20500..20600..20700..20800..20900..21000..21100..21200..21300..21400..21500..21600..21700..21800..21900..22000..22100..22200..22300..22400..22500..22600..22700..22800..22900..23000..23100..23200..23300..23400..23500..23600..23700..23800..23900..24000..24100..24200..24300..24400..24500..24600..24700..24800..24900..25000..25100..25200..25300..25400..25500..25600..25700..25800..25900..26000..26100..26200..26300..26400..26500..26600..26700..26800..26900..27000..27100..27200..27300..27400..27500..27600..27700..27800..27900..28000..28100..28200..28300..28400..28500..28600..28700..28800..28900..29000..29100..29200..29300..29400..29500..29600..29700..29800..29900..30000..30100..30200..30300..30400..30500..30600..30700..30800..30900..31000..31100..31200..31300..31400..31500..31600..31700..31800..31900..32000..32100..32200..32300..32400..32500..32600..32700..32800..32900..33000..33100..33200..33300..33400..33500..33600..33700..33800..33900..34000..34100..34200..34300..34400..34500..34600..34700..34800..34900..35000..35100..35200..35300..35400..35500..35600..35700..35800..35900..36000..36100..36200..36300..36400..36500..36600..36700..36800..36900..37000..37100..37200..37300..37400..37500..37600..37700..37800..37900..38000..38100..38200..38300..38400..38500..38600..38700..38800..38900..39000..39100..39200..39300..39400..39500..39600..39700..39800..39900..40000..40100..40200..40300..40400..40500..40600..40700..40800..40900..41000..41100..41200..41300..41400..41500..done
Runtime (without IO) in cpu-seconds: 0.03
Accuracy on test set: 40.19% (16687 correct, 24836 incorrect, 41523 total)
Precision/recall on test set: 100.00%/40.19%
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [4s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [3s]

===== 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
Reading model...OK. (8355 support vectors read)
Classifying test examples..100..200..300..400..500..600..700..800..900..1000..1100..1200..1300..1400..1500..1600..1700..1800..1900..2000..2100..2200..2300..2400..2500..2600..2700..2800..2900..3000..3100..3200..3300..3400..3500..3600..3700..3800..3900..4000..4100..4200..4300..4400..4500..4600..4700..4800..4900..5000..5100..5200..5300..5400..5500..5600..5700..5800..5900..6000..6100..6200..6300..6400..6500..6600..6700..6800..6900..7000..7100..7200..7300..7400..7500..7600..7700..7800..7900..8000..8100..8200..8300..8400..8500..8600..8700..8800..8900..9000..9100..9200..9300..9400..9500..9600..9700..9800..9900..10000..10100..10200..10300..10400..10500..10600..10700..10800..10900..11000..11100..11200..11300..11400..11500..11600..11700..11800..11900..12000..12100..12200..12300..12400..12500..12600..12700..12800..12900..13000..13100..13200..13300..13400..13500..13600..13700..13800..13900..14000..14100..14200..14300..14400..14500..14600..14700..14800..14900..15000..15100..15200..15300..15400..15500..15600..15700..15800..15900..16000..16100..16200..16300..16400..16500..16600..16700..16800..16900..17000..17100..17200..17300..17400..17500..17600..17700..17800..17900..18000..18100..18200..18300..18400..18500..18600..18700..18800..18900..19000..19100..19200..19300..19400..19500..19600..19700..19800..19900..20000..20100..20200..20300..20400..20500..20600..20700..20800..20900..21000..21100..21200..21300..21400..21500..21600..21700..done
Runtime (without IO) in cpu-seconds: 0.01
Accuracy on test set: 42.13% (9175 correct, 12604 incorrect, 21779 total)
Precision/recall on test set: 100.00%/42.13%
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [3s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s]


real	1m3.886s
user	1m0.692s
sys	0m1.752s

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