Reading training examples...done
Training set properties: 25 features, 90 rankings, 8156 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=0.521156
Iter 1: .........*(NumConst=1, SV=1, CEps=521.1556, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=406.6951, QPEps=0.0001)
Iter 3: .........*(NumConst=3, SV=3, CEps=1384.1213, QPEps=0.0010)
Iter 4: .........*(NumConst=4, SV=3, CEps=923.1675, QPEps=0.0006)
Iter 5: .........*(NumConst=5, SV=5, CEps=808.7879, QPEps=0.0008)
Iter 6: .........*(NumConst=6, SV=5, CEps=1579.3310, QPEps=0.0069)
Iter 7: .........*(NumConst=7, SV=5, CEps=1200.3371, QPEps=48.3528)
Iter 8: .........*(NumConst=8, SV=5, CEps=921.7301, QPEps=49.7186)
Iter 9: .........*(NumConst=9, SV=7, CEps=984.1246, QPEps=36.5490)
Iter 10: .........*(NumConst=10, SV=7, CEps=1757.5084, QPEps=3.5810)
Iter 11: .........*(NumConst=11, SV=8, CEps=642.5229, QPEps=42.0599)
Iter 12: .........*(NumConst=12, SV=9, CEps=290.8702, QPEps=44.3237)
Iter 13: .........*(NumConst=13, SV=10, CEps=341.6099, QPEps=0.5222)
Iter 14: .........*(NumConst=14, SV=10, CEps=294.9994, QPEps=17.1437)
Iter 15: .........*(NumConst=15, SV=9, CEps=162.1521, QPEps=0.0011)
Iter 16: .........*(NumConst=16, SV=10, CEps=152.2452, QPEps=0.0008)
Iter 17: .........*(NumConst=17, SV=9, CEps=164.2316, QPEps=37.9930)
Iter 18: .........*(NumConst=18, SV=10, CEps=134.8551, QPEps=7.7961)
Iter 19: .........*(NumConst=19, SV=9, CEps=170.6867, QPEps=48.7342)
Iter 20: .........*(NumConst=20, SV=9, CEps=117.0567, QPEps=0.0279)
Iter 21: .........*(NumConst=21, SV=8, CEps=82.4192, QPEps=4.6281)
Iter 22: .........*(NumConst=22, SV=8, CEps=104.7331, QPEps=1.5178)
Iter 23: .........*(NumConst=23, SV=9, CEps=101.3366, QPEps=9.4289)
Iter 24: .........*(NumConst=24, SV=10, CEps=84.5310, QPEps=0.0010)
Iter 25: .........*(NumConst=25, SV=10, CEps=99.5532, QPEps=27.8894)
Iter 26: .........*(NumConst=26, SV=10, CEps=58.7420, QPEps=6.8536)
Iter 27: .........*(NumConst=27, SV=11, CEps=65.5408, QPEps=12.7647)
Iter 28: .........*(NumConst=28, SV=12, CEps=63.4952, QPEps=28.9331)
Iter 29: .........*(NumConst=29, SV=10, CEps=73.6792, QPEps=25.8649)
Iter 30: .........*(NumConst=30, SV=9, CEps=87.8739, QPEps=17.6155)
Iter 31: .........*(NumConst=31, SV=11, CEps=42.2581, QPEps=12.1828)
Iter 32: .........*(NumConst=32, SV=10, CEps=82.4098, QPEps=15.8940)
Iter 33: .........*(NumConst=33, SV=10, CEps=63.2744, QPEps=12.7769)
Iter 34: .........*(NumConst=34, SV=12, CEps=70.0408, QPEps=14.4740)
Iter 35: .........*(NumConst=35, SV=12, CEps=47.7835, QPEps=8.8917)
Iter 36: .........*(NumConst=36, SV=10, CEps=40.1128, QPEps=0.0002)
Iter 37: .........*(NumConst=37, SV=11, CEps=46.3066, QPEps=10.8639)
Iter 38: .........*(NumConst=38, SV=10, CEps=64.8197, QPEps=10.3343)
Iter 39: .........*(NumConst=39, SV=9, CEps=46.0899, QPEps=0.0002)
Iter 40: .........*(NumConst=40, SV=9, CEps=43.3743, QPEps=5.6349)
Iter 41: .........*(NumConst=41, SV=11, CEps=30.5485, QPEps=12.0498)
Iter 42: .........*(NumConst=42, SV=12, CEps=30.9825, QPEps=8.8559)
Iter 43: .........*(NumConst=43, SV=10, CEps=22.2524, QPEps=1.4423)
Iter 44: .........*(NumConst=44, SV=10, CEps=28.8845, QPEps=3.6054)
Iter 45: .........*(NumConst=45, SV=12, CEps=20.3776, QPEps=5.2588)
Iter 46: .........*(NumConst=46, SV=9, CEps=34.5789, QPEps=4.0433)
Iter 47: .........*(NumConst=47, SV=9, CEps=18.4100, QPEps=0.0001)
Iter 48: .........*(NumConst=48, SV=9, CEps=17.0375, QPEps=0.0001)
Iter 49: .........*(NumConst=49, SV=9, CEps=19.8268, QPEps=0.0001)
Iter 50: .........*(NumConst=50, SV=10, CEps=20.9722, QPEps=0.0002)
Iter 51: .........*(NumConst=51, SV=11, CEps=14.2202, QPEps=5.9111)
Iter 52: .........*(NumConst=52, SV=12, CEps=9.8777, QPEps=1.8805)
Iter 53: .........*(NumConst=53, SV=10, CEps=19.2109, QPEps=0.0000)
Iter 54: .........*(NumConst=54, SV=11, CEps=14.9202, QPEps=3.9416)
Iter 55: .........*(NumConst=55, SV=13, CEps=13.8815, QPEps=4.4342)
Iter 56: .........*(NumConst=56, SV=12, CEps=18.7263, QPEps=1.5566)
Iter 57: .........*(NumConst=57, SV=15, CEps=9.1750, QPEps=2.5008)
Iter 58: .........*(NumConst=58, SV=18, CEps=15.4764, QPEps=3.4524)
Iter 59: .........*(NumConst=59, SV=14, CEps=17.5243, QPEps=4.3244)
Iter 60: .........*(NumConst=60, SV=14, CEps=14.0719, QPEps=4.0310)
Iter 61: .........*(NumConst=61, SV=15, CEps=18.6737, QPEps=3.7353)
Iter 62: .........*(NumConst=61, SV=13, CEps=10.0219, QPEps=2.8732)
Iter 63: .........*(NumConst=61, SV=16, CEps=10.0648, QPEps=3.9013)
Iter 64: .........*(NumConst=60, SV=14, CEps=10.3728, QPEps=3.8342)
Iter 65: .........*(NumConst=61, SV=13, CEps=10.3397, QPEps=3.9108)
Iter 66: .........*(NumConst=60, SV=12, CEps=6.2463, QPEps=1.4270)
Iter 67: .........*(NumConst=59, SV=13, CEps=6.3443, QPEps=3.0924)
Iter 68: .........*(NumConst=59, SV=10, CEps=6.2370, QPEps=0.0002)
Iter 69: .........*(NumConst=59, SV=12, CEps=4.7926, QPEps=2.2999)
Iter 70: .........*(NumConst=58, SV=12, CEps=9.4351, QPEps=0.8594)
Iter 71: .........*(NumConst=58, SV=12, CEps=5.4531, QPEps=1.8556)
Iter 72: .........*(NumConst=59, SV=13, CEps=6.1134, QPEps=2.1840)
Iter 73: .........*(NumConst=60, SV=13, CEps=4.1172, QPEps=1.8433)
Iter 74: .........*(NumConst=61, SV=13, CEps=5.7835, QPEps=1.8858)
Iter 75: .........*(NumConst=61, SV=12, CEps=6.3095, QPEps=0.4066)
Iter 76: .........*(NumConst=62, SV=12, CEps=3.3518, QPEps=0.2321)
Iter 77: .........*(NumConst=63, SV=13, CEps=4.5779, QPEps=1.1694)
Iter 78: .........*(NumConst=63, SV=13, CEps=5.2196, QPEps=1.5805)
Iter 79: .........*(NumConst=63, SV=13, CEps=3.7618, QPEps=0.8041)
Iter 80: .........*(NumConst=62, SV=12, CEps=3.8916, QPEps=1.6150)
Iter 81: .........*(NumConst=62, SV=13, CEps=3.6724, QPEps=0.6989)
Iter 82: .........*(NumConst=63, SV=12, CEps=4.0639, QPEps=0.0549)
Iter 83: .........*(NumConst=64, SV=12, CEps=3.1230, QPEps=1.0264)
Iter 84: .........*(NumConst=63, SV=13, CEps=2.3754, QPEps=0.8463)
Iter 85: .........*(NumConst=60, SV=13, CEps=3.2394, QPEps=0.6189)
Iter 86: .........*(NumConst=61, SV=13, CEps=2.2299, QPEps=1.0402)
Iter 87: .........*(NumConst=60, SV=13, CEps=3.0400, QPEps=0.7453)
Iter 88: .........*(NumConst=61, SV=14, CEps=2.0106, QPEps=0.7501)
Iter 89: .........*(NumConst=62, SV=15, CEps=2.0404, QPEps=0.8503)
Iter 90: .........*(NumConst=63, SV=14, CEps=2.7898, QPEps=0.5390)
Iter 91: .........*(NumConst=63, SV=14, CEps=2.1975, QPEps=0.8466)
Iter 92: .........*(NumConst=61, SV=13, CEps=2.1781, QPEps=0.5582)
Iter 93: .........*(NumConst=61, SV=14, CEps=1.7325, QPEps=0.7123)
Iter 94: .........*(NumConst=61, SV=13, CEps=2.0033, QPEps=0.8366)
Iter 95: .........*(NumConst=58, SV=15, CEps=1.1193, QPEps=0.3256)
Iter 96: .........*(NumConst=59, SV=14, CEps=1.4007, QPEps=0.4599)
Iter 97: .........*(NumConst=60, SV=14, CEps=2.0321, QPEps=0.4800)
Iter 98: .........*(NumConst=61, SV=16, CEps=1.2058, QPEps=0.4414)
Iter 99: .........*(NumConst=62, SV=15, CEps=1.4083, QPEps=0.5594)
Iter 100: .........*(NumConst=63, SV=14, CEps=0.8560, QPEps=0.2527)
Iter 101: .........*(NumConst=63, SV=14, CEps=0.9417, QPEps=0.2792)
Iter 102: .........*(NumConst=63, SV=15, CEps=0.8294, QPEps=0.0907)
Iter 103: .........*(NumConst=64, SV=15, CEps=0.8238, QPEps=0.2326)
Iter 104: .........*(NumConst=65, SV=17, CEps=1.0351, QPEps=0.3957)
Iter 105: .........*(NumConst=66, SV=16, CEps=0.9372, QPEps=0.2201)
Iter 106: .........*(NumConst=67, SV=17, CEps=0.7675, QPEps=0.3040)
Iter 107: .........*(NumConst=68, SV=17, CEps=0.6812, QPEps=0.1652)
Iter 108: .........*(NumConst=67, SV=16, CEps=0.6660, QPEps=0.2785)
Iter 109: .........*(NumConst=67, SV=15, CEps=0.5931, QPEps=0.2882)
Iter 110: .........*(NumConst=67, SV=16, CEps=0.5631, QPEps=0.2684)
Iter 111: .........*(NumConst=67, SV=15, CEps=0.8498, QPEps=0.2329)
Iter 112: .........*(NumConst=68, SV=14, CEps=0.6178, QPEps=0.0638)
Iter 113: .........(NumConst=68, SV=14, CEps=0.4728, QPEps=0.0638)
Final epsilon on KKT-Conditions: 0.47278
Upper bound on duality gap: 0.46594
Dual objective value: dval=309.90750
Primal objective value: pval=310.37344
Total number of constraints in final working set: 68 (of 112)
Number of iterations: 113
Number of calls to 'find_most_violated_constraint': 10170
Number of SV: 14 
Norm of weight vector: |w|=1.93064
Value of slack variable (on working set): xi=308.10076
Value of slack variable (global): xi=308.50975
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=455.60586
Runtime in cpu-seconds: 0.71
Compacting linear model...done
Writing learned model...done