Reading training examples...done
Training set properties: 49 features, 180 rankings, 15544 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=1.014872
Iter 1: .........*(NumConst=1, SV=1, CEps=1014.8722, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=1699.7111, QPEps=0.0003)
Iter 3: .........*(NumConst=3, SV=3, CEps=1634.8786, QPEps=0.0003)
Iter 4: .........*(NumConst=4, SV=4, CEps=1594.2396, QPEps=0.0082)
Iter 5: .........*(NumConst=5, SV=4, CEps=1340.4713, QPEps=0.0024)
Iter 6: .........*(NumConst=6, SV=5, CEps=1187.3537, QPEps=0.0100)
Iter 7: .........*(NumConst=7, SV=5, CEps=1461.7518, QPEps=48.3540)
Iter 8: .........*(NumConst=8, SV=6, CEps=1420.0538, QPEps=49.8618)
Iter 9: .........*(NumConst=9, SV=6, CEps=1525.0311, QPEps=49.4885)
Iter 10: .........*(NumConst=10, SV=8, CEps=785.5434, QPEps=49.9801)
Iter 11: .........*(NumConst=11, SV=7, CEps=560.0195, QPEps=3.5226)
Iter 12: .........*(NumConst=12, SV=9, CEps=373.2140, QPEps=0.0128)
Iter 13: .........*(NumConst=13, SV=10, CEps=634.3279, QPEps=26.0648)
Iter 14: .........*(NumConst=14, SV=9, CEps=345.0723, QPEps=0.0043)
Iter 15: .........*(NumConst=15, SV=9, CEps=300.7336, QPEps=1.4812)
Iter 16: .........*(NumConst=16, SV=9, CEps=249.9220, QPEps=0.0044)
Iter 17: .........*(NumConst=17, SV=10, CEps=298.4126, QPEps=9.7292)
Iter 18: .........*(NumConst=18, SV=9, CEps=376.9198, QPEps=9.6890)
Iter 19: .........*(NumConst=19, SV=8, CEps=202.5760, QPEps=0.1274)
Iter 20: .........*(NumConst=20, SV=9, CEps=199.1265, QPEps=0.0008)
Iter 21: .........*(NumConst=21, SV=10, CEps=172.3542, QPEps=0.0007)
Iter 22: .........*(NumConst=22, SV=8, CEps=185.4948, QPEps=8.9722)
Iter 23: .........*(NumConst=23, SV=9, CEps=141.6252, QPEps=43.4860)
Iter 24: .........*(NumConst=24, SV=9, CEps=206.6001, QPEps=7.5150)
Iter 25: .........*(NumConst=25, SV=12, CEps=99.9673, QPEps=32.6200)
Iter 26: .........*(NumConst=26, SV=10, CEps=126.1981, QPEps=0.0001)
Iter 27: .........*(NumConst=27, SV=9, CEps=121.1697, QPEps=8.2018)
Iter 28: .........*(NumConst=28, SV=10, CEps=119.6725, QPEps=0.0018)
Iter 29: .........*(NumConst=29, SV=11, CEps=112.5900, QPEps=42.8590)
Iter 30: .........*(NumConst=30, SV=11, CEps=93.9545, QPEps=29.7715)
Iter 31: .........*(NumConst=31, SV=12, CEps=83.8992, QPEps=39.2376)
Iter 32: .........*(NumConst=32, SV=12, CEps=65.4966, QPEps=15.1936)
Iter 33: .........*(NumConst=33, SV=12, CEps=95.7056, QPEps=2.8835)
Iter 34: .........*(NumConst=34, SV=11, CEps=72.2381, QPEps=6.1381)
Iter 35: .........*(NumConst=35, SV=11, CEps=58.3692, QPEps=8.7024)
Iter 36: .........*(NumConst=36, SV=12, CEps=64.2087, QPEps=2.9511)
Iter 37: .........*(NumConst=37, SV=13, CEps=54.8095, QPEps=25.4374)
Iter 38: .........*(NumConst=38, SV=12, CEps=58.5212, QPEps=5.5122)
Iter 39: .........*(NumConst=39, SV=12, CEps=52.9332, QPEps=5.1081)
Iter 40: .........*(NumConst=40, SV=13, CEps=35.0585, QPEps=6.0010)
Iter 41: .........*(NumConst=41, SV=14, CEps=54.0484, QPEps=9.3212)
Iter 42: .........*(NumConst=42, SV=14, CEps=43.9625, QPEps=12.7152)
Iter 43: .........*(NumConst=43, SV=12, CEps=47.3609, QPEps=2.9646)
Iter 44: .........*(NumConst=44, SV=10, CEps=32.5784, QPEps=0.0002)
Iter 45: .........*(NumConst=45, SV=10, CEps=34.1545, QPEps=14.1078)
Iter 46: .........*(NumConst=46, SV=13, CEps=46.1773, QPEps=14.4268)
Iter 47: .........*(NumConst=47, SV=12, CEps=22.0633, QPEps=9.6241)
Iter 48: .........*(NumConst=48, SV=11, CEps=48.3352, QPEps=4.5768)
Iter 49: .........*(NumConst=49, SV=13, CEps=39.5445, QPEps=10.3568)
Iter 50: .........*(NumConst=50, SV=11, CEps=23.5342, QPEps=4.8059)
Iter 51: .........*(NumConst=51, SV=11, CEps=21.3305, QPEps=0.0000)
Iter 52: .........*(NumConst=52, SV=11, CEps=24.1651, QPEps=7.2488)
Iter 53: .........*(NumConst=53, SV=13, CEps=17.8270, QPEps=6.3118)
Iter 54: .........*(NumConst=54, SV=11, CEps=24.0083, QPEps=0.0000)
Iter 55: .........*(NumConst=55, SV=12, CEps=15.3020, QPEps=0.0002)
Iter 56: .........*(NumConst=55, SV=12, CEps=16.1158, QPEps=1.0968)
Iter 57: .........*(NumConst=56, SV=12, CEps=14.4803, QPEps=0.0002)
Iter 58: .........*(NumConst=57, SV=11, CEps=12.2390, QPEps=3.1505)
Iter 59: .........*(NumConst=58, SV=13, CEps=8.9737, QPEps=3.7539)
Iter 60: .........*(NumConst=58, SV=13, CEps=15.8134, QPEps=2.2304)
Iter 61: .........*(NumConst=59, SV=13, CEps=14.7830, QPEps=2.4198)
Iter 62: .........*(NumConst=60, SV=14, CEps=12.3085, QPEps=2.2186)
Iter 63: .........*(NumConst=59, SV=13, CEps=8.8557, QPEps=0.4646)
Iter 64: .........*(NumConst=59, SV=12, CEps=13.5962, QPEps=0.0000)
Iter 65: .........*(NumConst=59, SV=11, CEps=9.3197, QPEps=0.5815)
Iter 66: .........*(NumConst=60, SV=13, CEps=7.8987, QPEps=2.7754)
Iter 67: .........*(NumConst=59, SV=13, CEps=11.1439, QPEps=1.9243)
Iter 68: .........*(NumConst=59, SV=13, CEps=6.4747, QPEps=2.5320)
Iter 69: .........*(NumConst=60, SV=13, CEps=8.6897, QPEps=0.0000)
Iter 70: .........*(NumConst=60, SV=13, CEps=5.8900, QPEps=1.5008)
Iter 71: .........*(NumConst=59, SV=13, CEps=5.8691, QPEps=0.4198)
Iter 72: .........*(NumConst=60, SV=13, CEps=4.7096, QPEps=2.3309)
Iter 73: .........*(NumConst=60, SV=14, CEps=5.4507, QPEps=2.1148)
Iter 74: .........*(NumConst=61, SV=13, CEps=4.2183, QPEps=1.1400)
Iter 75: .........*(NumConst=59, SV=17, CEps=4.1756, QPEps=1.5279)
Iter 76: .........*(NumConst=60, SV=15, CEps=11.9964, QPEps=0.8720)
Iter 77: .........*(NumConst=61, SV=16, CEps=4.9531, QPEps=1.1053)
Iter 78: .........*(NumConst=62, SV=13, CEps=4.5504, QPEps=0.0000)
Iter 79: .........*(NumConst=63, SV=13, CEps=2.6216, QPEps=0.0000)
Iter 80: .........*(NumConst=64, SV=15, CEps=4.4468, QPEps=0.3769)
Iter 81: .........*(NumConst=63, SV=15, CEps=3.5761, QPEps=0.0000)
Iter 82: .........*(NumConst=63, SV=14, CEps=3.5946, QPEps=0.1551)
Iter 83: .........*(NumConst=62, SV=17, CEps=2.3751, QPEps=0.1206)
Iter 84: .........*(NumConst=62, SV=17, CEps=3.7205, QPEps=0.2745)
Iter 85: .........*(NumConst=63, SV=17, CEps=2.2368, QPEps=0.5057)
Iter 86: .........*(NumConst=64, SV=16, CEps=2.7259, QPEps=0.5918)
Iter 87: .........*(NumConst=64, SV=16, CEps=3.2571, QPEps=0.0950)
Iter 88: .........*(NumConst=65, SV=16, CEps=1.8040, QPEps=0.0242)
Iter 89: .........*(NumConst=65, SV=16, CEps=2.2112, QPEps=0.8148)
Iter 90: .........*(NumConst=65, SV=16, CEps=2.1031, QPEps=0.0000)
Iter 91: .........*(NumConst=65, SV=17, CEps=4.5034, QPEps=0.5862)
Iter 92: .........*(NumConst=62, SV=17, CEps=1.9556, QPEps=0.1289)
Iter 93: .........*(NumConst=61, SV=17, CEps=1.8212, QPEps=0.1347)
Iter 94: .........(NumConst=61, SV=17, CEps=0.9944, QPEps=0.1347)
Final epsilon on KKT-Conditions: 0.99437
Upper bound on duality gap: 0.07100
Dual objective value: dval=41.00342
Primal objective value: pval=41.07443
Total number of constraints in final working set: 61 (of 93)
Number of iterations: 94
Number of calls to 'find_most_violated_constraint': 16920
Number of SV: 17 
Norm of weight vector: |w|=1.63867
Value of slack variable (on working set): xi=566.60303
Value of slack variable (global): xi=567.59731
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=3030.27054
Runtime in cpu-seconds: 1.65
Compacting linear model...done
Writing learned model...done