Reading training examples...done
Training set properties: 49 features, 90 rankings, 8163 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=0.527100
Iter 1: .........*(NumConst=1, SV=1, CEps=527.1000, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=1439.7612, QPEps=0.0000)
Iter 3: .........*(NumConst=3, SV=3, CEps=743.5076, QPEps=0.0007)
Iter 4: .........*(NumConst=4, SV=4, CEps=1839.6298, QPEps=0.0017)
Iter 5: .........*(NumConst=5, SV=4, CEps=742.8815, QPEps=0.0032)
Iter 6: .........*(NumConst=6, SV=6, CEps=472.4245, QPEps=0.0028)
Iter 7: .........*(NumConst=7, SV=6, CEps=914.3757, QPEps=0.0012)
Iter 8: .........*(NumConst=8, SV=7, CEps=947.1794, QPEps=0.0045)
Iter 9: .........*(NumConst=9, SV=7, CEps=356.9963, QPEps=6.8886)
Iter 10: .........*(NumConst=10, SV=8, CEps=321.4385, QPEps=8.5236)
Iter 11: .........*(NumConst=11, SV=8, CEps=243.3399, QPEps=5.2806)
Iter 12: .........*(NumConst=12, SV=8, CEps=210.5873, QPEps=4.9809)
Iter 13: .........*(NumConst=13, SV=8, CEps=149.2233, QPEps=0.0070)
Iter 14: .........*(NumConst=14, SV=9, CEps=146.9356, QPEps=0.2757)
Iter 15: .........*(NumConst=15, SV=8, CEps=147.2657, QPEps=0.0037)
Iter 16: .........*(NumConst=16, SV=9, CEps=155.3590, QPEps=0.0023)
Iter 17: .........*(NumConst=17, SV=9, CEps=101.8948, QPEps=0.0007)
Iter 18: .........*(NumConst=18, SV=9, CEps=133.4392, QPEps=0.0012)
Iter 19: .........*(NumConst=19, SV=9, CEps=96.7660, QPEps=0.0017)
Iter 20: .........*(NumConst=20, SV=9, CEps=87.1946, QPEps=0.0029)
Iter 21: .........*(NumConst=21, SV=9, CEps=76.6041, QPEps=35.4820)
Iter 22: .........*(NumConst=22, SV=9, CEps=90.6185, QPEps=0.0009)
Iter 23: .........*(NumConst=23, SV=9, CEps=67.3180, QPEps=0.0018)
Iter 24: .........*(NumConst=24, SV=8, CEps=62.1923, QPEps=2.0349)
Iter 25: .........*(NumConst=25, SV=9, CEps=65.4104, QPEps=0.0003)
Iter 26: .........*(NumConst=26, SV=9, CEps=43.2722, QPEps=0.0004)
Iter 27: .........*(NumConst=27, SV=9, CEps=43.0565, QPEps=0.0007)
Iter 28: .........*(NumConst=28, SV=9, CEps=42.8950, QPEps=0.0002)
Iter 29: .........*(NumConst=29, SV=10, CEps=33.1008, QPEps=0.0001)
Iter 30: .........*(NumConst=30, SV=10, CEps=36.9561, QPEps=5.4095)
Iter 31: .........*(NumConst=31, SV=10, CEps=42.9922, QPEps=0.0000)
Iter 32: .........*(NumConst=32, SV=12, CEps=29.4434, QPEps=5.8573)
Iter 33: .........*(NumConst=33, SV=11, CEps=29.8982, QPEps=0.2665)
Iter 34: .........*(NumConst=34, SV=11, CEps=23.3149, QPEps=4.0318)
Iter 35: .........*(NumConst=35, SV=11, CEps=31.1293, QPEps=9.3888)
Iter 36: .........*(NumConst=36, SV=10, CEps=18.5053, QPEps=8.7032)
Iter 37: .........*(NumConst=37, SV=10, CEps=21.4225, QPEps=7.2658)
Iter 38: .........*(NumConst=38, SV=10, CEps=21.8817, QPEps=2.5475)
Iter 39: .........*(NumConst=39, SV=11, CEps=21.7709, QPEps=9.1875)
Iter 40: .........*(NumConst=40, SV=11, CEps=18.3411, QPEps=5.0184)
Iter 41: .........*(NumConst=41, SV=11, CEps=15.7593, QPEps=5.9272)
Iter 42: .........*(NumConst=42, SV=10, CEps=17.9544, QPEps=1.8144)
Iter 43: .........*(NumConst=43, SV=12, CEps=11.2466, QPEps=2.4411)
Iter 44: .........*(NumConst=44, SV=10, CEps=19.2046, QPEps=3.7264)
Iter 45: .........*(NumConst=45, SV=10, CEps=15.8831, QPEps=3.1012)
Iter 46: .........*(NumConst=46, SV=11, CEps=11.0517, QPEps=2.4834)
Iter 47: .........*(NumConst=47, SV=11, CEps=12.0684, QPEps=2.3456)
Iter 48: .........*(NumConst=48, SV=12, CEps=8.5843, QPEps=1.1882)
Iter 49: .........*(NumConst=49, SV=12, CEps=12.1917, QPEps=2.9512)
Iter 50: .........*(NumConst=50, SV=12, CEps=8.1493, QPEps=2.5027)
Iter 51: .........*(NumConst=51, SV=12, CEps=12.1564, QPEps=3.0064)
Iter 52: .........*(NumConst=52, SV=12, CEps=6.2039, QPEps=2.8212)
Iter 53: .........*(NumConst=53, SV=11, CEps=10.1058, QPEps=0.4809)
Iter 54: .........*(NumConst=54, SV=10, CEps=8.4823, QPEps=2.5451)
Iter 55: .........*(NumConst=55, SV=10, CEps=5.9882, QPEps=0.3800)
Iter 56: .........*(NumConst=56, SV=9, CEps=5.3998, QPEps=0.0000)
Iter 57: .........*(NumConst=56, SV=10, CEps=6.8568, QPEps=0.0000)
Iter 58: .........*(NumConst=56, SV=12, CEps=4.4691, QPEps=1.5355)
Iter 59: .........*(NumConst=57, SV=12, CEps=5.0851, QPEps=1.4906)
Iter 60: .........*(NumConst=57, SV=11, CEps=4.9850, QPEps=0.7093)
Iter 61: .........*(NumConst=58, SV=10, CEps=3.8613, QPEps=0.0000)
Iter 62: .........*(NumConst=58, SV=11, CEps=2.9740, QPEps=0.0000)
Iter 63: .........*(NumConst=58, SV=11, CEps=3.7266, QPEps=0.0000)
Iter 64: .........*(NumConst=57, SV=10, CEps=2.9403, QPEps=0.0000)
Iter 65: .........*(NumConst=58, SV=10, CEps=2.6965, QPEps=0.0000)
Iter 66: .........*(NumConst=58, SV=12, CEps=2.6980, QPEps=0.7313)
Iter 67: .........*(NumConst=58, SV=9, CEps=3.5762, QPEps=0.1619)
Iter 68: .........*(NumConst=58, SV=9, CEps=2.2186, QPEps=0.0000)
Iter 69: .........*(NumConst=58, SV=11, CEps=1.7053, QPEps=0.0900)
Iter 70: .........*(NumConst=59, SV=9, CEps=2.5768, QPEps=0.0000)
Iter 71: .........*(NumConst=59, SV=9, CEps=1.7918, QPEps=0.0000)
Iter 72: .........*(NumConst=59, SV=10, CEps=1.5998, QPEps=0.3378)
Iter 73: .........*(NumConst=58, SV=11, CEps=2.0171, QPEps=0.3213)
Iter 74: .........*(NumConst=59, SV=11, CEps=1.7988, QPEps=0.7218)
Iter 75: .........*(NumConst=59, SV=11, CEps=1.7967, QPEps=0.0849)
Iter 76: .........*(NumConst=60, SV=11, CEps=1.4288, QPEps=0.2113)
Iter 77: .........*(NumConst=61, SV=11, CEps=1.1406, QPEps=0.5533)
Iter 78: .........*(NumConst=61, SV=10, CEps=1.5928, QPEps=0.0670)
Iter 79: .........*(NumConst=61, SV=10, CEps=1.0710, QPEps=0.3841)
Iter 80: .........*(NumConst=61, SV=11, CEps=1.2992, QPEps=0.3701)
Iter 81: .........*(NumConst=62, SV=11, CEps=1.1110, QPEps=0.4799)
Iter 82: .........*(NumConst=62, SV=11, CEps=1.3798, QPEps=0.3019)
Iter 83: .........*(NumConst=61, SV=12, CEps=0.9412, QPEps=0.1491)
Iter 84: .........*(NumConst=61, SV=10, CEps=0.7424, QPEps=0.3425)
Iter 85: .........*(NumConst=60, SV=12, CEps=1.8093, QPEps=0.0181)
Iter 86: .........*(NumConst=60, SV=13, CEps=1.1913, QPEps=0.2617)
Iter 87: .........*(NumConst=60, SV=13, CEps=0.9161, QPEps=0.3190)
Iter 88: .........*(NumConst=61, SV=13, CEps=0.6348, QPEps=0.0960)
Iter 89: .........*(NumConst=61, SV=10, CEps=0.6070, QPEps=0.0410)
Iter 90: .........*(NumConst=61, SV=10, CEps=0.8007, QPEps=0.0000)
Iter 91: .........(NumConst=61, SV=10, CEps=0.5082, QPEps=0.0000)
Final epsilon on KKT-Conditions: 0.50822
Upper bound on duality gap: 0.05082
Dual objective value: dval=29.85509
Primal objective value: pval=29.90591
Total number of constraints in final working set: 61 (of 90)
Number of iterations: 91
Number of calls to 'find_most_violated_constraint': 8190
Number of SV: 10 
Norm of weight vector: |w|=1.88214
Value of slack variable (on working set): xi=280.83857
Value of slack variable (global): xi=281.34678
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=973.24880
Runtime in cpu-seconds: 0.29
Compacting linear model...done
Writing learned model...done