Reading training examples...done
Training set properties: 25 features, 90 rankings, 8184 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=0.486067
Iter 1: .........*(NumConst=1, SV=1, CEps=486.0667, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=373.1738, QPEps=0.0002)
Iter 3: .........*(NumConst=3, SV=3, CEps=1671.3460, QPEps=0.0005)
Iter 4: .........*(NumConst=4, SV=3, CEps=886.2058, QPEps=0.0011)
Iter 5: .........*(NumConst=5, SV=4, CEps=661.2579, QPEps=0.0035)
Iter 6: .........*(NumConst=6, SV=6, CEps=1598.3697, QPEps=0.0022)
Iter 7: .........*(NumConst=7, SV=5, CEps=1314.5647, QPEps=27.4314)
Iter 8: .........*(NumConst=8, SV=6, CEps=1008.2555, QPEps=48.8828)
Iter 9: .........*(NumConst=9, SV=7, CEps=1092.3007, QPEps=43.3920)
Iter 10: .........*(NumConst=10, SV=7, CEps=1040.1757, QPEps=44.8562)
Iter 11: .........*(NumConst=11, SV=7, CEps=982.4070, QPEps=49.3229)
Iter 12: .........*(NumConst=12, SV=8, CEps=433.0863, QPEps=1.1343)
Iter 13: .........*(NumConst=13, SV=8, CEps=299.5289, QPEps=21.9595)
Iter 14: .........*(NumConst=14, SV=9, CEps=390.6506, QPEps=0.0084)
Iter 15: .........*(NumConst=15, SV=10, CEps=239.6240, QPEps=33.3275)
Iter 16: .........*(NumConst=16, SV=10, CEps=156.5399, QPEps=22.2511)
Iter 17: .........*(NumConst=17, SV=10, CEps=226.8787, QPEps=47.9231)
Iter 18: .........*(NumConst=18, SV=9, CEps=105.1956, QPEps=32.4119)
Iter 19: .........*(NumConst=19, SV=8, CEps=141.5175, QPEps=0.8249)
Iter 20: .........*(NumConst=20, SV=12, CEps=113.8263, QPEps=28.5483)
Iter 21: .........*(NumConst=21, SV=10, CEps=157.7027, QPEps=0.0001)
Iter 22: .........*(NumConst=22, SV=9, CEps=128.7136, QPEps=24.5805)
Iter 23: .........*(NumConst=23, SV=10, CEps=109.8446, QPEps=0.0004)
Iter 24: .........*(NumConst=24, SV=11, CEps=108.3347, QPEps=47.2324)
Iter 25: .........*(NumConst=25, SV=11, CEps=98.2874, QPEps=0.0003)
Iter 26: .........*(NumConst=26, SV=12, CEps=104.4833, QPEps=36.1361)
Iter 27: .........*(NumConst=27, SV=12, CEps=126.5020, QPEps=14.8031)
Iter 28: .........*(NumConst=28, SV=12, CEps=65.1836, QPEps=19.8651)
Iter 29: .........*(NumConst=29, SV=11, CEps=50.6519, QPEps=15.5865)
Iter 30: .........*(NumConst=30, SV=12, CEps=60.3893, QPEps=19.1867)
Iter 31: .........*(NumConst=31, SV=11, CEps=52.0691, QPEps=12.4311)
Iter 32: .........*(NumConst=32, SV=10, CEps=50.9010, QPEps=14.0892)
Iter 33: .........*(NumConst=33, SV=10, CEps=94.7514, QPEps=9.8802)
Iter 34: .........*(NumConst=34, SV=11, CEps=34.4682, QPEps=7.4257)
Iter 35: .........*(NumConst=35, SV=11, CEps=61.3917, QPEps=10.1681)
Iter 36: .........*(NumConst=36, SV=11, CEps=40.5425, QPEps=2.1094)
Iter 37: .........*(NumConst=37, SV=11, CEps=38.2569, QPEps=11.0288)
Iter 38: .........*(NumConst=38, SV=11, CEps=32.5280, QPEps=13.5470)
Iter 39: .........*(NumConst=39, SV=14, CEps=29.1635, QPEps=14.4934)
Iter 40: .........*(NumConst=40, SV=12, CEps=36.4825, QPEps=13.7157)
Iter 41: .........*(NumConst=41, SV=12, CEps=34.9154, QPEps=14.4445)
Iter 42: .........*(NumConst=42, SV=11, CEps=26.6430, QPEps=5.3144)
Iter 43: .........*(NumConst=43, SV=11, CEps=26.0383, QPEps=10.7494)
Iter 44: .........*(NumConst=44, SV=12, CEps=22.9426, QPEps=8.7687)
Iter 45: .........*(NumConst=45, SV=11, CEps=24.1418, QPEps=8.8716)
Iter 46: .........*(NumConst=46, SV=12, CEps=26.8763, QPEps=10.4690)
Iter 47: .........*(NumConst=47, SV=11, CEps=13.9975, QPEps=2.4757)
Iter 48: .........*(NumConst=48, SV=13, CEps=19.2034, QPEps=6.1975)
Iter 49: .........*(NumConst=49, SV=11, CEps=18.2821, QPEps=6.3153)
Iter 50: .........*(NumConst=50, SV=12, CEps=24.7782, QPEps=4.0247)
Iter 51: .........*(NumConst=51, SV=13, CEps=15.2819, QPEps=3.9747)
Iter 52: .........*(NumConst=52, SV=11, CEps=13.5556, QPEps=5.3961)
Iter 53: .........*(NumConst=53, SV=13, CEps=24.7236, QPEps=5.6860)
Iter 54: .........*(NumConst=54, SV=13, CEps=11.1440, QPEps=4.4620)
Iter 55: .........*(NumConst=55, SV=11, CEps=17.3388, QPEps=0.0123)
Iter 56: .........*(NumConst=56, SV=11, CEps=13.4971, QPEps=5.5459)
Iter 57: .........*(NumConst=57, SV=12, CEps=21.3830, QPEps=4.5224)
Iter 58: .........*(NumConst=58, SV=14, CEps=10.2444, QPEps=3.6178)
Iter 59: .........*(NumConst=59, SV=10, CEps=11.0994, QPEps=1.2636)
Iter 60: .........*(NumConst=60, SV=13, CEps=7.3366, QPEps=1.6129)
Iter 61: .........*(NumConst=60, SV=12, CEps=11.7172, QPEps=2.9151)
Iter 62: .........*(NumConst=60, SV=11, CEps=10.2472, QPEps=1.8251)
Iter 63: .........*(NumConst=61, SV=11, CEps=7.6420, QPEps=0.8792)
Iter 64: .........*(NumConst=62, SV=11, CEps=9.2545, QPEps=2.3503)
Iter 65: .........*(NumConst=62, SV=12, CEps=7.3133, QPEps=2.2138)
Iter 66: .........*(NumConst=61, SV=11, CEps=9.8361, QPEps=1.4821)
Iter 67: .........*(NumConst=61, SV=11, CEps=7.4811, QPEps=2.1917)
Iter 68: .........*(NumConst=61, SV=11, CEps=7.4091, QPEps=3.6276)
Iter 69: .........*(NumConst=62, SV=14, CEps=6.2801, QPEps=3.1265)
Iter 70: .........*(NumConst=60, SV=15, CEps=9.1522, QPEps=2.6890)
Iter 71: .........*(NumConst=59, SV=13, CEps=8.2139, QPEps=2.7578)
Iter 72: .........*(NumConst=60, SV=13, CEps=4.3680, QPEps=1.4657)
Iter 73: .........*(NumConst=60, SV=16, CEps=5.4928, QPEps=1.3854)
Iter 74: .........*(NumConst=60, SV=16, CEps=8.6691, QPEps=2.0562)
Iter 75: .........*(NumConst=61, SV=13, CEps=7.4845, QPEps=2.0248)
Iter 76: .........*(NumConst=61, SV=12, CEps=4.8180, QPEps=1.4657)
Iter 77: .........*(NumConst=61, SV=12, CEps=7.4444, QPEps=1.6809)
Iter 78: .........*(NumConst=61, SV=12, CEps=3.4823, QPEps=1.3906)
Iter 79: .........*(NumConst=62, SV=12, CEps=3.3736, QPEps=1.5362)
Iter 80: .........*(NumConst=62, SV=16, CEps=3.8353, QPEps=1.4438)
Iter 81: .........*(NumConst=62, SV=11, CEps=5.3637, QPEps=1.5040)
Iter 82: .........*(NumConst=63, SV=12, CEps=4.8159, QPEps=1.1097)
Iter 83: .........*(NumConst=63, SV=11, CEps=3.1978, QPEps=0.9719)
Iter 84: .........*(NumConst=62, SV=10, CEps=3.0821, QPEps=0.1350)
Iter 85: .........*(NumConst=63, SV=10, CEps=2.8134, QPEps=0.2667)
Iter 86: .........*(NumConst=63, SV=10, CEps=1.8813, QPEps=0.6172)
Iter 87: .........*(NumConst=64, SV=12, CEps=2.6986, QPEps=0.8704)
Iter 88: .........*(NumConst=64, SV=13, CEps=2.9077, QPEps=0.4764)
Iter 89: .........*(NumConst=64, SV=12, CEps=5.2906, QPEps=0.7876)
Iter 90: .........*(NumConst=63, SV=12, CEps=2.3763, QPEps=0.5507)
Iter 91: .........*(NumConst=62, SV=12, CEps=3.1218, QPEps=0.7035)
Iter 92: .........*(NumConst=63, SV=12, CEps=2.4341, QPEps=0.3606)
Iter 93: .........*(NumConst=63, SV=11, CEps=1.7234, QPEps=0.7670)
Iter 94: .........*(NumConst=62, SV=15, CEps=1.6541, QPEps=0.7881)
Iter 95: .........*(NumConst=63, SV=15, CEps=2.5835, QPEps=0.8213)
Iter 96: .........*(NumConst=64, SV=13, CEps=1.8027, QPEps=0.7659)
Iter 97: .........*(NumConst=65, SV=13, CEps=1.0486, QPEps=0.2948)
Iter 98: .........*(NumConst=64, SV=13, CEps=1.8729, QPEps=0.2931)
Iter 99: .........*(NumConst=65, SV=12, CEps=1.6379, QPEps=0.4718)
Iter 100: .........*(NumConst=65, SV=13, CEps=0.8288, QPEps=0.2687)
Iter 101: .........*(NumConst=64, SV=13, CEps=1.5718, QPEps=0.0917)
Iter 102: .........*(NumConst=65, SV=14, CEps=1.3166, QPEps=0.2551)
Iter 103: .........*(NumConst=63, SV=14, CEps=2.1620, QPEps=0.3939)
Iter 104: .........*(NumConst=62, SV=14, CEps=1.1973, QPEps=0.2539)
Iter 105: .........*(NumConst=63, SV=13, CEps=0.9089, QPEps=0.3639)
Iter 106: .........*(NumConst=64, SV=11, CEps=2.2736, QPEps=0.3567)
Iter 107: .........*(NumConst=65, SV=13, CEps=0.8420, QPEps=0.3799)
Iter 108: .........*(NumConst=63, SV=11, CEps=1.3591, QPEps=0.2462)
Iter 109: .........*(NumConst=64, SV=12, CEps=0.7996, QPEps=0.3570)
Iter 110: .........*(NumConst=62, SV=12, CEps=1.5655, QPEps=0.1528)
Iter 111: .........*(NumConst=61, SV=12, CEps=0.9704, QPEps=0.0326)
Iter 112: .........*(NumConst=61, SV=11, CEps=0.8763, QPEps=0.1708)
Iter 113: .........*(NumConst=62, SV=11, CEps=0.8746, QPEps=0.1715)
Iter 114: .........(NumConst=62, SV=11, CEps=0.4816, QPEps=0.1715)
Final epsilon on KKT-Conditions: 0.48160
Upper bound on duality gap: 0.53918
Dual objective value: dval=283.55627
Primal objective value: pval=284.09546
Total number of constraints in final working set: 62 (of 113)
Number of iterations: 114
Number of calls to 'find_most_violated_constraint': 10260
Number of SV: 11 
Norm of weight vector: |w|=2.51778
Value of slack variable (on working set): xi=280.44427
Value of slack variable (global): xi=280.92584
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=212.15609
Runtime in cpu-seconds: 0.41
Compacting linear model...done
Writing learned model...done