Reading training examples...done
Training set properties: 104 features, 90 rankings, 8151 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=0.536978
Iter 1: .........*(NumConst=1, SV=1, CEps=536.9778, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=368.5768, QPEps=0.0000)
Iter 3: .........*(NumConst=3, SV=2, CEps=580.4970, QPEps=0.0000)
Iter 4: .........*(NumConst=4, SV=3, CEps=1013.6318, QPEps=0.0000)
Iter 5: .........*(NumConst=5, SV=4, CEps=411.6068, QPEps=0.0000)
Iter 6: .........*(NumConst=6, SV=6, CEps=931.0914, QPEps=0.0005)
Iter 7: .........*(NumConst=7, SV=5, CEps=1421.2221, QPEps=0.0004)
Iter 8: .........*(NumConst=8, SV=5, CEps=653.7738, QPEps=0.0009)
Iter 9: .........*(NumConst=9, SV=6, CEps=550.8566, QPEps=0.5442)
Iter 10: .........*(NumConst=10, SV=6, CEps=670.7849, QPEps=38.7390)
Iter 11: .........*(NumConst=11, SV=7, CEps=266.1531, QPEps=8.3899)
Iter 12: .........*(NumConst=12, SV=10, CEps=348.5293, QPEps=0.0002)
Iter 13: .........*(NumConst=13, SV=9, CEps=182.7980, QPEps=0.0001)
Iter 14: .........*(NumConst=14, SV=10, CEps=119.8055, QPEps=1.1683)
Iter 15: .........*(NumConst=15, SV=8, CEps=172.2712, QPEps=24.2201)
Iter 16: .........*(NumConst=16, SV=9, CEps=119.7547, QPEps=0.0000)
Iter 17: .........*(NumConst=17, SV=8, CEps=103.8410, QPEps=0.0003)
Iter 18: .........*(NumConst=18, SV=10, CEps=123.2929, QPEps=0.0001)
Iter 19: .........*(NumConst=19, SV=9, CEps=125.6079, QPEps=0.0006)
Iter 20: .........*(NumConst=20, SV=9, CEps=93.1986, QPEps=2.6604)
Iter 21: .........*(NumConst=21, SV=8, CEps=61.4834, QPEps=28.6849)
Iter 22: .........*(NumConst=22, SV=9, CEps=142.2521, QPEps=0.0001)
Iter 23: .........*(NumConst=23, SV=9, CEps=86.7239, QPEps=21.1280)
Iter 24: .........*(NumConst=24, SV=9, CEps=91.7871, QPEps=0.0001)
Iter 25: .........*(NumConst=25, SV=9, CEps=53.5945, QPEps=0.0001)
Iter 26: .........*(NumConst=26, SV=8, CEps=70.8343, QPEps=4.7630)
Iter 27: .........*(NumConst=27, SV=8, CEps=38.3837, QPEps=17.7255)
Iter 28: .........*(NumConst=28, SV=9, CEps=40.3322, QPEps=0.0000)
Iter 29: .........*(NumConst=29, SV=9, CEps=37.9648, QPEps=0.0000)
Iter 30: .........*(NumConst=30, SV=9, CEps=49.5951, QPEps=0.0001)
Iter 31: .........*(NumConst=31, SV=9, CEps=29.8362, QPEps=0.0005)
Iter 32: .........*(NumConst=32, SV=11, CEps=23.1526, QPEps=0.0000)
Iter 33: .........*(NumConst=33, SV=13, CEps=24.2959, QPEps=10.5205)
Iter 34: .........*(NumConst=34, SV=13, CEps=35.1832, QPEps=6.0520)
Iter 35: .........*(NumConst=35, SV=13, CEps=29.8497, QPEps=7.3608)
Iter 36: .........*(NumConst=36, SV=11, CEps=19.8082, QPEps=0.0000)
Iter 37: .........*(NumConst=37, SV=11, CEps=18.1604, QPEps=6.0095)
Iter 38: .........*(NumConst=38, SV=12, CEps=28.4600, QPEps=0.3166)
Iter 39: .........*(NumConst=39, SV=12, CEps=17.4339, QPEps=4.7051)
Iter 40: .........*(NumConst=40, SV=12, CEps=17.1625, QPEps=8.1224)
Iter 41: .........*(NumConst=41, SV=11, CEps=12.8778, QPEps=0.0000)
Iter 42: .........*(NumConst=42, SV=11, CEps=11.9203, QPEps=0.9124)
Iter 43: .........*(NumConst=43, SV=11, CEps=14.8736, QPEps=0.0000)
Iter 44: .........*(NumConst=44, SV=12, CEps=10.2372, QPEps=0.1401)
Iter 45: .........*(NumConst=45, SV=12, CEps=12.7322, QPEps=4.9699)
Iter 46: .........*(NumConst=46, SV=12, CEps=9.9688, QPEps=0.3921)
Iter 47: .........*(NumConst=47, SV=12, CEps=9.8540, QPEps=4.7815)
Iter 48: .........*(NumConst=48, SV=12, CEps=7.6429, QPEps=0.0000)
Iter 49: .........*(NumConst=49, SV=12, CEps=11.2165, QPEps=2.8367)
Iter 50: .........*(NumConst=50, SV=12, CEps=8.9438, QPEps=3.2850)
Iter 51: .........*(NumConst=51, SV=13, CEps=5.4777, QPEps=1.8814)
Iter 52: .........*(NumConst=52, SV=13, CEps=11.0697, QPEps=2.4275)
Iter 53: .........*(NumConst=53, SV=13, CEps=10.2270, QPEps=0.9369)
Iter 54: .........*(NumConst=54, SV=13, CEps=5.3954, QPEps=0.4224)
Iter 55: .........*(NumConst=55, SV=13, CEps=9.8059, QPEps=2.1903)
Iter 56: .........*(NumConst=55, SV=12, CEps=6.5415, QPEps=0.0000)
Iter 57: .........*(NumConst=56, SV=12, CEps=6.5188, QPEps=0.0001)
Iter 58: .........*(NumConst=57, SV=12, CEps=5.9198, QPEps=0.8828)
Iter 59: .........*(NumConst=57, SV=12, CEps=3.9759, QPEps=0.0000)
Iter 60: .........*(NumConst=58, SV=15, CEps=5.9668, QPEps=0.6745)
Iter 61: .........*(NumConst=59, SV=13, CEps=4.9506, QPEps=0.5840)
Iter 62: .........*(NumConst=59, SV=13, CEps=3.1140, QPEps=1.1942)
Iter 63: .........*(NumConst=60, SV=13, CEps=3.2180, QPEps=0.9901)
Iter 64: .........*(NumConst=58, SV=12, CEps=4.5204, QPEps=0.0000)
Iter 65: .........*(NumConst=59, SV=12, CEps=2.8434, QPEps=0.0000)
Iter 66: .........*(NumConst=58, SV=13, CEps=2.9530, QPEps=0.0000)
Iter 67: .........*(NumConst=59, SV=14, CEps=2.1820, QPEps=0.2105)
Iter 68: .........*(NumConst=58, SV=15, CEps=3.2109, QPEps=0.6837)
Iter 69: .........*(NumConst=58, SV=14, CEps=3.1431, QPEps=0.7518)
Iter 70: .........*(NumConst=58, SV=14, CEps=2.3333, QPEps=0.9718)
Iter 71: .........*(NumConst=59, SV=15, CEps=2.2879, QPEps=1.0151)
Iter 72: .........*(NumConst=59, SV=12, CEps=1.4851, QPEps=0.0000)
Iter 73: .........*(NumConst=59, SV=12, CEps=2.4640, QPEps=0.2651)
Iter 74: .........*(NumConst=59, SV=13, CEps=3.6080, QPEps=0.4962)
Iter 75: .........*(NumConst=59, SV=12, CEps=1.6347, QPEps=0.1341)
Iter 76: .........*(NumConst=59, SV=13, CEps=1.9401, QPEps=0.3515)
Iter 77: .........*(NumConst=60, SV=14, CEps=1.4478, QPEps=0.0000)
Iter 78: .........*(NumConst=61, SV=15, CEps=2.1214, QPEps=0.0000)
Iter 79: .........*(NumConst=62, SV=16, CEps=1.3960, QPEps=0.5104)
Iter 80: .........*(NumConst=63, SV=14, CEps=1.7688, QPEps=0.2622)
Iter 81: .........*(NumConst=64, SV=13, CEps=0.8720, QPEps=0.2071)
Iter 82: .........*(NumConst=63, SV=15, CEps=1.8885, QPEps=0.2665)
Iter 83: .........*(NumConst=62, SV=13, CEps=1.5888, QPEps=0.4107)
Iter 84: .........*(NumConst=62, SV=14, CEps=1.2158, QPEps=0.3029)
Iter 85: .........*(NumConst=61, SV=13, CEps=2.2689, QPEps=0.0000)
Iter 86: .........*(NumConst=61, SV=14, CEps=1.0298, QPEps=0.2773)
Iter 87: .........*(NumConst=62, SV=15, CEps=1.1710, QPEps=0.0000)
Iter 88: .........*(NumConst=62, SV=14, CEps=0.8091, QPEps=0.0000)
Iter 89: .........*(NumConst=61, SV=14, CEps=0.6515, QPEps=0.0000)
Iter 90: .........(NumConst=61, SV=14, CEps=0.5143, QPEps=0.0000)
Final epsilon on KKT-Conditions: 0.51428
Upper bound on duality gap: 0.00514
Dual objective value: dval=2.58080
Primal objective value: pval=2.58594
Total number of constraints in final working set: 61 (of 89)
Number of iterations: 90
Number of calls to 'find_most_violated_constraint': 8100
Number of SV: 14 
Norm of weight vector: |w|=0.51438
Value of slack variable (on working set): xi=244.85086
Value of slack variable (global): xi=245.36514
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=1270.85323
Runtime in cpu-seconds: 0.45
Compacting linear model...done
Writing learned model...done