ServerRun 39789
Creatorchuertas
Programsvmlight-linear
DatasetGoodStudents
Task typeBinaryClassification
Created2y42d ago
Done! Flag_green
24m20s
165M
MulticlassClassification
23m3s
0.175
40s
0.178
25s

Log file

===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset3/train
===== One versus all: training label y=1 versus the rest =====
=== START _one-vs-all-learner1: ./run learn ../data1
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..41600..41700..41800..41900..42000..42100..42200..42300..42400..42500..42600..42700..42800..42900..43000..43100..43200..43300..43400..43500..43600..43700..43800..43900..44000..44100..44200..44300..44400..44500..44600..44700..44800..44900..45000..45100..45200..45300..45400..45500..45600..45700..45800..45900..46000..46100..46200..46300..46400..46500..46600..46700..46800..46900..47000..47100..47200..47300..47400..47500..47600..47700..47800..47900..48000..48100..48200..48300..48400..48500..48600..48700..48800..48900..49000..49100..49200..49300..49400..49500..49600..49700..49800..49900..50000..50100..50200..50300..50400..50500..50600..50700..50800..50900..51000..51100..51200..51300..51400..51500..51600..51700..51800..51900..52000..52100..52200..52300..52400..52500..52600..52700..52800..52900..53000..53100..53200..53300..53400..53500..53600..53700..53800..53900..54000..54100..54200..54300..54400..54500..54600..54700..54800..54900..55000..55100..55200..55300..55400..55500..55600..55700..55800..55900..56000..56100..56200..56300..56400..56500..56600..56700..56800..56900..57000..57100..57200..57300..57400..57500..57600..57700..57800..57900..58000..58100..58200..58300..58400..58500..58600..58700..58800..58900..59000..59100..59200..59300..59400..59500..59600..59700..59800..59900..60000..60100..60200..60300..60400..60500..60600..60700..60800..60900..61000..61100..61200..61300..61400..61500..61600..61700..61800..61900..62000..62100..62200..62300..62400..62500..62600..62700..62800..62900..63000..63100..63200..63300..63400..63500..63600..63700..63800..63900..64000..64100..64200..64300..64400..64500..64600..64700..64800..64900..65000..65100..65200..65300..65400..65500..65600..65700..65800..65900..66000..66100..66200..66300..66400..66500..66600..66700..66800..66900..67000..67100..67200..67300..67400..67500..67600..67700..67800..67900..68000..68100..68200..68300..68400..68500..68600..68700..68800..68900..69000..69100..69200..69300..69400..69500..69600..69700..69800..69900..70000..70100..70200..70300..70400..70500..70600..70700..70800..70900..71000..71100..71200..71300..71400..71500..71600..71700..71800..71900..72000..72100..72200..72300..72400..72500..72600..72700..72800..72900..73000..73100..73200..73300..73400..73500..73600..73700..73800..73900..74000..74100..74200..74300..74400..74500..74600..74700..74800..74900..75000..75100..75200..75300..75400..75500..75600..75700..75800..75900..76000..76100..76200..76300..76400..76500..76600..76700..76800..76900..77000..77100..77200..77300..77400..77500..77600..77700..77800..77900..78000..78100..78200..78300..78400..78500..78600..78700..78800..78900..79000..79100..79200..79300..79400..79500..79600..79700..79800..79900..80000..80100..80200..80300..80400..80500..80600..80700..80800..80900..81000..81100..81200..81300..81400..81500..81600..81700..81800..81900..82000..82100..82200..82300..82400..82500..82600..82700..82800..82900..83000..83100..83200..83300..83400..83500..83600..83700..83800..83900..84000..84100..84200..84300..OK. (84379 examples read)
Setting default regularization parameter C=0.0000
Optimizing..............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................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..........................................................................................................................................................................................................................................................................................................................done. (10305 iterations)
Optimization finished (12481 misclassified, maxdiff=0.00078).
Runtime in cpu-seconds: 585.04
Number of SV: 28680 (including 28669 at upper bound)
L1 loss: loss=28047.67935
Norm of weight vector: |w|=0.00877
Norm of longest example vector: |x|=13103.55771
Estimated VCdim of classifier: VCdim<=4414.56429
Computing XiAlpha-estimates...done
Runtime for XiAlpha-estimates in cpu-seconds: 0.12
XiAlpha-estimate of the error: error<=33.99% (rho=1.00,depth=0)
XiAlpha-estimate of the recall: recall=>78.59% (rho=1.00,depth=0)
XiAlpha-estimate of the precision: precision=>78.59% (rho=1.00,depth=0)
Number of kernel evaluations: 1495794
Writing model file...done
=== END _one-vs-all-learner1: ./run learn ../data1 --- OK [612s]

===== One versus all: training label y=2 versus the rest =====
=== START _one-vs-all-learner2: ./run learn ../data2
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..41600..41700..41800..41900..42000..42100..42200..42300..42400..42500..42600..42700..42800..42900..43000..43100..43200..43300..43400..43500..43600..43700..43800..43900..44000..44100..44200..44300..44400..44500..44600..44700..44800..44900..45000..45100..45200..45300..45400..45500..45600..45700..45800..45900..46000..46100..46200..46300..46400..46500..46600..46700..46800..46900..47000..47100..47200..47300..47400..47500..47600..47700..47800..47900..48000..48100..48200..48300..48400..48500..48600..48700..48800..48900..49000..49100..49200..49300..49400..49500..49600..49700..49800..49900..50000..50100..50200..50300..50400..50500..50600..50700..50800..50900..51000..51100..51200..51300..51400..51500..51600..51700..51800..51900..52000..52100..52200..52300..52400..52500..52600..52700..52800..52900..53000..53100..53200..53300..53400..53500..53600..53700..53800..53900..54000..54100..54200..54300..54400..54500..54600..54700..54800..54900..55000..55100..55200..55300..55400..55500..55600..55700..55800..55900..56000..56100..56200..56300..56400..56500..56600..56700..56800..56900..57000..57100..57200..57300..57400..57500..57600..57700..57800..57900..58000..58100..58200..58300..58400..58500..58600..58700..58800..58900..59000..59100..59200..59300..59400..59500..59600..59700..59800..59900..60000..60100..60200..60300..60400..60500..60600..60700..60800..60900..61000..61100..61200..61300..61400..61500..61600..61700..61800..61900..62000..62100..62200..62300..62400..62500..62600..62700..62800..62900..63000..63100..63200..63300..63400..63500..63600..63700..63800..63900..64000..64100..64200..64300..64400..64500..64600..64700..64800..64900..65000..65100..65200..65300..65400..65500..65600..65700..65800..65900..66000..66100..66200..66300..66400..66500..66600..66700..66800..66900..67000..67100..67200..67300..67400..67500..67600..67700..67800..67900..68000..68100..68200..68300..68400..68500..68600..68700..68800..68900..69000..69100..69200..69300..69400..69500..69600..69700..69800..69900..70000..70100..70200..70300..70400..70500..70600..70700..70800..70900..71000..71100..71200..71300..71400..71500..71600..71700..71800..71900..72000..72100..72200..72300..72400..72500..72600..72700..72800..72900..73000..73100..73200..73300..73400..73500..73600..73700..73800..73900..74000..74100..74200..74300..74400..74500..74600..74700..74800..74900..75000..75100..75200..75300..75400..75500..75600..75700..75800..75900..76000..76100..76200..76300..76400..76500..76600..76700..76800..76900..77000..77100..77200..77300..77400..77500..77600..77700..77800..77900..78000..78100..78200..78300..78400..78500..78600..78700..78800..78900..79000..79100..79200..79300..79400..79500..79600..79700..79800..79900..80000..80100..80200..80300..80400..80500..80600..80700..80800..80900..81000..81100..81200..81300..81400..81500..81600..81700..81800..81900..82000..82100..82200..82300..82400..82500..82600..82700..82800..82900..83000..83100..83200..83300..83400..83500..83600..83700..83800..83900..84000..84100..84200..84300..OK. (84379 examples read)
Setting default regularization parameter C=0.0000
Optimizing..............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................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(13278 iterations)
Optimization finished (12477 misclassified, maxdiff=0.00093).
Runtime in cpu-seconds: 726.51
Number of SV: 28681 (including 28669 at upper bound)
L1 loss: loss=28047.82111
Norm of weight vector: |w|=0.00877
Norm of longest example vector: |x|=13103.55771
Estimated VCdim of classifier: VCdim<=4412.81813
Computing XiAlpha-estimates...done
Runtime for XiAlpha-estimates in cpu-seconds: 0.03
XiAlpha-estimate of the error: error<=33.99% (rho=1.00,depth=0)
XiAlpha-estimate of the recall: recall=>17.66% (rho=1.00,depth=0)
XiAlpha-estimate of the precision: precision=>17.66% (rho=1.00,depth=0)
Number of kernel evaluations: 1658856
Writing model file...done
=== END _one-vs-all-learner2: ./run learn ../data2 --- OK [757s]

=== END program1: ./run learn ../dataset3/train --- OK [1383s]

===== MAIN: predict/evaluate on train data =====
=== START program4: ./run stripLabels ../dataset3/train ../program0/evalTrain.in
=== END program4: ./run stripLabels ../dataset3/train ../program0/evalTrain.in --- OK [3s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
=== START _one-vs-all-learner1: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y1
Reading model...OK. (28680 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..41600..41700..41800..41900..42000..42100..42200..42300..42400..42500..42600..42700..42800..42900..43000..43100..43200..43300..43400..43500..43600..43700..43800..43900..44000..44100..44200..44300..44400..44500..44600..44700..44800..44900..45000..45100..45200..45300..45400..45500..45600..45700..45800..45900..46000..46100..46200..46300..46400..46500..46600..46700..46800..46900..47000..47100..47200..47300..47400..47500..47600..47700..47800..47900..48000..48100..48200..48300..48400..48500..48600..48700..48800..48900..49000..49100..49200..49300..49400..49500..49600..49700..49800..49900..50000..50100..50200..50300..50400..50500..50600..50700..50800..50900..51000..51100..51200..51300..51400..51500..51600..51700..51800..51900..52000..52100..52200..52300..52400..52500..52600..52700..52800..52900..53000..53100..53200..53300..53400..53500..53600..53700..53800..53900..54000..54100..54200..54300..54400..54500..54600..54700..54800..54900..55000..55100..55200..55300..55400..55500..55600..55700..55800..55900..56000..56100..56200..56300..56400..56500..56600..56700..56800..56900..57000..57100..57200..57300..57400..57500..57600..57700..57800..57900..58000..58100..58200..58300..58400..58500..58600..58700..58800..58900..59000..59100..59200..59300..59400..59500..59600..59700..59800..59900..60000..60100..60200..60300..60400..60500..60600..60700..60800..60900..61000..61100..61200..61300..61400..61500..61600..61700..61800..61900..62000..62100..62200..62300..62400..62500..62600..62700..62800..62900..63000..63100..63200..63300..63400..63500..63600..63700..63800..63900..64000..64100..64200..64300..64400..64500..64600..64700..64800..64900..65000..65100..65200..65300..65400..65500..65600..65700..65800..65900..66000..66100..66200..66300..66400..66500..66600..66700..66800..66900..67000..67100..67200..67300..67400..67500..67600..67700..67800..67900..68000..68100..68200..68300..68400..68500..68600..68700..68800..68900..69000..69100..69200..69300..69400..69500..69600..69700..69800..69900..70000..70100..70200..70300..70400..70500..70600..70700..70800..70900..71000..71100..71200..71300..71400..71500..71600..71700..71800..71900..72000..72100..72200..72300..72400..72500..72600..72700..72800..72900..73000..73100..73200..73300..73400..73500..73600..73700..73800..73900..74000..74100..74200..74300..74400..74500..74600..74700..74800..74900..75000..75100..75200..75300..75400..75500..75600..75700..75800..75900..76000..76100..76200..76300..76400..76500..76600..76700..76800..76900..77000..77100..77200..77300..77400..77500..77600..77700..77800..77900..78000..78100..78200..78300..78400..78500..78600..78700..78800..78900..79000..79100..79200..79300..79400..79500..79600..79700..79800..79900..80000..80100..80200..80300..80400..80500..80600..80700..80800..80900..81000..81100..81200..81300..81400..81500..81600..81700..81800..81900..82000..82100..82200..82300..82400..82500..82600..82700..82800..82900..83000..83100..83200..83300..83400..83500..83600..83700..83800..83900..84000..84100..84200..84300..done
Runtime (without IO) in cpu-seconds: 0.06
Accuracy on test set: 89.38% (75421 correct, 8958 incorrect, 84379 total)
Precision/recall on test set: 100.00%/89.38%
=== END _one-vs-all-learner1: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y1 --- OK [19s]
=== START _one-vs-all-learner2: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y2
Reading model...OK. (28681 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..41600..41700..41800..41900..42000..42100..42200..42300..42400..42500..42600..42700..42800..42900..43000..43100..43200..43300..43400..43500..43600..43700..43800..43900..44000..44100..44200..44300..44400..44500..44600..44700..44800..44900..45000..45100..45200..45300..45400..45500..45600..45700..45800..45900..46000..46100..46200..46300..46400..46500..46600..46700..46800..46900..47000..47100..47200..47300..47400..47500..47600..47700..47800..47900..48000..48100..48200..48300..48400..48500..48600..48700..48800..48900..49000..49100..49200..49300..49400..49500..49600..49700..49800..49900..50000..50100..50200..50300..50400..50500..50600..50700..50800..50900..51000..51100..51200..51300..51400..51500..51600..51700..51800..51900..52000..52100..52200..52300..52400..52500..52600..52700..52800..52900..53000..53100..53200..53300..53400..53500..53600..53700..53800..53900..54000..54100..54200..54300..54400..54500..54600..54700..54800..54900..55000..55100..55200..55300..55400..55500..55600..55700..55800..55900..56000..56100..56200..56300..56400..56500..56600..56700..56800..56900..57000..57100..57200..57300..57400..57500..57600..57700..57800..57900..58000..58100..58200..58300..58400..58500..58600..58700..58800..58900..59000..59100..59200..59300..59400..59500..59600..59700..59800..59900..60000..60100..60200..60300..60400..60500..60600..60700..60800..60900..61000..61100..61200..61300..61400..61500..61600..61700..61800..61900..62000..62100..62200..62300..62400..62500..62600..62700..62800..62900..63000..63100..63200..63300..63400..63500..63600..63700..63800..63900..64000..64100..64200..64300..64400..64500..64600..64700..64800..64900..65000..65100..65200..65300..65400..65500..65600..65700..65800..65900..66000..66100..66200..66300..66400..66500..66600..66700..66800..66900..67000..67100..67200..67300..67400..67500..67600..67700..67800..67900..68000..68100..68200..68300..68400..68500..68600..68700..68800..68900..69000..69100..69200..69300..69400..69500..69600..69700..69800..69900..70000..70100..70200..70300..70400..70500..70600..70700..70800..70900..71000..71100..71200..71300..71400..71500..71600..71700..71800..71900..72000..72100..72200..72300..72400..72500..72600..72700..72800..72900..73000..73100..73200..73300..73400..73500..73600..73700..73800..73900..74000..74100..74200..74300..74400..74500..74600..74700..74800..74900..75000..75100..75200..75300..75400..75500..75600..75700..75800..75900..76000..76100..76200..76300..76400..76500..76600..76700..76800..76900..77000..77100..77200..77300..77400..77500..77600..77700..77800..77900..78000..78100..78200..78300..78400..78500..78600..78700..78800..78900..79000..79100..79200..79300..79400..79500..79600..79700..79800..79900..80000..80100..80200..80300..80400..80500..80600..80700..80800..80900..81000..81100..81200..81300..81400..81500..81600..81700..81800..81900..82000..82100..82200..82300..82400..82500..82600..82700..82800..82900..83000..83100..83200..83300..83400..83500..83600..83700..83800..83900..84000..84100..84200..84300..done
Runtime (without IO) in cpu-seconds: 0.03
Accuracy on test set: 10.62% (8962 correct, 75417 incorrect, 84379 total)
Precision/recall on test set: 100.00%/10.62%
=== END _one-vs-all-learner2: ./run predict ../../program0/evalTrain.in ../../program0/evalTrain.out-y2 --- OK [20s]
84379 examples
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [40s]
=== START program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out
=== END program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out --- OK [8s]

===== MAIN: predict/evaluate on test data =====
=== START program4: ./run stripLabels ../dataset3/test ../program0/evalTest.in
=== END program4: ./run stripLabels ../dataset3/test ../program0/evalTest.in --- OK [1s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
=== START _one-vs-all-learner1: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y1
Reading model...OK. (28680 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..done
Runtime (without IO) in cpu-seconds: 0.01
Accuracy on test set: 89.49% (32363 correct, 3800 incorrect, 36163 total)
Precision/recall on test set: 100.00%/89.49%
=== END _one-vs-all-learner1: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y1 --- OK [11s]
=== START _one-vs-all-learner2: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y2
Reading model...OK. (28681 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..done
Runtime (without IO) in cpu-seconds: 0.18
Accuracy on test set: 10.52% (3804 correct, 32359 incorrect, 36163 total)
Precision/recall on test set: 100.00%/10.52%
=== END _one-vs-all-learner2: ./run predict ../../program0/evalTest.in ../../program0/evalTest.out-y2 --- OK [13s]
36163 examples
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [25s]
=== START program5: ./run evaluate ../dataset3/test ../program0/evalTest.out
=== END program5: ./run evaluate ../dataset3/test ../program0/evalTest.out --- OK [4s]


real	24m24.140s
user	23m43.325s
sys	0m11.225s

Run specification Arrow_right
Results Arrow_right


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