Reading training examples...done
Training set properties: 25 features, 180 rankings, 15673 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=0.998928
Iter 1: .........*(NumConst=1, SV=1, CEps=998.9278, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=755.2356, QPEps=0.0001)
Iter 3: .........*(NumConst=3, SV=2, CEps=1289.6130, QPEps=0.0004)
Iter 4: .........*(NumConst=4, SV=3, CEps=1304.5654, QPEps=0.0070)
Iter 5: .........*(NumConst=5, SV=4, CEps=2407.5343, QPEps=0.0149)
Iter 6: .........*(NumConst=6, SV=4, CEps=3783.6802, QPEps=43.0711)
Iter 7: .........*(NumConst=7, SV=5, CEps=1802.0641, QPEps=0.0633)
Iter 8: .........*(NumConst=8, SV=7, CEps=4072.1995, QPEps=0.0463)
Iter 9: .........*(NumConst=9, SV=8, CEps=1360.0367, QPEps=0.0224)
Iter 10: .........*(NumConst=10, SV=8, CEps=559.0012, QPEps=0.0111)
Iter 11: .........*(NumConst=11, SV=9, CEps=647.4041, QPEps=18.3921)
Iter 12: .........*(NumConst=12, SV=9, CEps=365.1384, QPEps=0.0032)
Iter 13: .........*(NumConst=13, SV=8, CEps=696.8593, QPEps=0.0082)
Iter 14: .........*(NumConst=14, SV=9, CEps=326.9218, QPEps=23.1878)
Iter 15: .........*(NumConst=15, SV=9, CEps=320.5009, QPEps=49.3397)
Iter 16: .........*(NumConst=16, SV=10, CEps=473.5810, QPEps=0.0008)
Iter 17: .........*(NumConst=17, SV=10, CEps=301.8197, QPEps=0.0011)
Iter 18: .........*(NumConst=18, SV=10, CEps=296.4963, QPEps=0.0014)
Iter 19: .........*(NumConst=19, SV=10, CEps=225.9330, QPEps=0.0056)
Iter 20: .........*(NumConst=20, SV=10, CEps=308.2943, QPEps=40.6722)
Iter 21: .........*(NumConst=21, SV=8, CEps=354.3698, QPEps=7.5493)
Iter 22: .........*(NumConst=22, SV=8, CEps=319.2576, QPEps=2.6860)
Iter 23: .........*(NumConst=23, SV=8, CEps=212.0529, QPEps=8.8146)
Iter 24: .........*(NumConst=24, SV=8, CEps=134.3831, QPEps=23.9568)
Iter 25: .........*(NumConst=25, SV=10, CEps=250.7673, QPEps=0.0009)
Iter 26: .........*(NumConst=26, SV=12, CEps=165.1488, QPEps=45.6434)
Iter 27: .........*(NumConst=27, SV=9, CEps=222.9928, QPEps=0.0007)
Iter 28: .........*(NumConst=28, SV=8, CEps=136.3226, QPEps=48.7726)
Iter 29: .........*(NumConst=29, SV=8, CEps=142.5863, QPEps=27.2747)
Iter 30: .........*(NumConst=30, SV=10, CEps=140.3925, QPEps=0.0004)
Iter 31: .........*(NumConst=31, SV=10, CEps=79.2283, QPEps=0.4490)
Iter 32: .........*(NumConst=32, SV=11, CEps=105.9534, QPEps=31.7835)
Iter 33: .........*(NumConst=33, SV=11, CEps=120.4272, QPEps=34.8311)
Iter 34: .........*(NumConst=34, SV=11, CEps=117.3082, QPEps=23.5168)
Iter 35: .........*(NumConst=35, SV=11, CEps=82.9354, QPEps=35.9743)
Iter 36: .........*(NumConst=36, SV=10, CEps=58.7469, QPEps=1.7472)
Iter 37: .........*(NumConst=37, SV=11, CEps=85.3653, QPEps=29.2269)
Iter 38: .........*(NumConst=38, SV=11, CEps=68.4640, QPEps=2.8798)
Iter 39: .........*(NumConst=39, SV=12, CEps=55.0356, QPEps=4.9735)
Iter 40: .........*(NumConst=40, SV=12, CEps=52.5135, QPEps=0.0001)
Iter 41: .........*(NumConst=41, SV=10, CEps=58.2559, QPEps=0.0001)
Iter 42: .........*(NumConst=42, SV=12, CEps=39.4400, QPEps=15.8337)
Iter 43: .........*(NumConst=43, SV=12, CEps=57.4936, QPEps=1.0719)
Iter 44: .........*(NumConst=44, SV=14, CEps=32.1598, QPEps=13.9658)
Iter 45: .........*(NumConst=45, SV=14, CEps=35.4448, QPEps=5.8142)
Iter 46: .........*(NumConst=46, SV=13, CEps=68.7933, QPEps=9.6179)
Iter 47: .........*(NumConst=47, SV=15, CEps=37.2161, QPEps=11.9344)
Iter 48: .........*(NumConst=48, SV=16, CEps=52.3515, QPEps=13.7423)
Iter 49: .........*(NumConst=49, SV=13, CEps=27.1751, QPEps=2.7976)
Iter 50: .........*(NumConst=50, SV=13, CEps=37.3565, QPEps=10.5630)
Iter 51: .........*(NumConst=51, SV=12, CEps=29.0918, QPEps=3.6002)
Iter 52: .........*(NumConst=52, SV=14, CEps=25.8373, QPEps=8.8799)
Iter 53: .........*(NumConst=53, SV=13, CEps=21.5625, QPEps=1.2679)
Iter 54: .........*(NumConst=54, SV=13, CEps=24.6701, QPEps=7.2775)
Iter 55: .........*(NumConst=55, SV=12, CEps=34.6446, QPEps=5.6852)
Iter 56: .........*(NumConst=56, SV=13, CEps=13.8012, QPEps=5.5638)
Iter 57: .........*(NumConst=56, SV=11, CEps=25.1657, QPEps=3.0815)
Iter 58: .........*(NumConst=57, SV=12, CEps=25.6896, QPEps=6.7208)
Iter 59: .........*(NumConst=58, SV=11, CEps=24.0046, QPEps=0.0001)
Iter 60: .........*(NumConst=59, SV=11, CEps=16.4560, QPEps=0.1701)
Iter 61: .........*(NumConst=59, SV=12, CEps=17.0570, QPEps=3.8681)
Iter 62: .........*(NumConst=58, SV=12, CEps=17.2506, QPEps=3.9173)
Iter 63: .........*(NumConst=59, SV=13, CEps=11.1870, QPEps=0.1674)
Iter 64: .........*(NumConst=59, SV=13, CEps=15.3468, QPEps=4.0418)
Iter 65: .........*(NumConst=60, SV=12, CEps=17.7465, QPEps=2.1360)
Iter 66: .........*(NumConst=60, SV=14, CEps=10.9292, QPEps=2.6832)
Iter 67: .........*(NumConst=60, SV=12, CEps=12.6611, QPEps=1.5209)
Iter 68: .........*(NumConst=60, SV=11, CEps=10.8437, QPEps=0.0000)
Iter 69: .........*(NumConst=61, SV=10, CEps=8.8913, QPEps=0.0000)
Iter 70: .........*(NumConst=60, SV=11, CEps=6.7349, QPEps=0.5755)
Iter 71: .........*(NumConst=61, SV=11, CEps=18.5468, QPEps=1.9768)
Iter 72: .........*(NumConst=62, SV=12, CEps=8.0173, QPEps=3.3674)
Iter 73: .........*(NumConst=62, SV=12, CEps=9.2024, QPEps=0.0000)
Iter 74: .........*(NumConst=63, SV=12, CEps=5.9727, QPEps=0.2587)
Iter 75: .........*(NumConst=63, SV=12, CEps=8.4538, QPEps=2.2578)
Iter 76: .........*(NumConst=62, SV=11, CEps=6.1884, QPEps=1.8190)
Iter 77: .........*(NumConst=63, SV=11, CEps=4.5268, QPEps=0.0000)
Iter 78: .........*(NumConst=64, SV=14, CEps=5.7382, QPEps=1.6987)
Iter 79: .........*(NumConst=65, SV=12, CEps=7.5953, QPEps=1.7198)
Iter 80: .........*(NumConst=64, SV=12, CEps=6.5871, QPEps=0.1918)
Iter 81: .........*(NumConst=62, SV=11, CEps=4.7888, QPEps=0.0000)
Iter 82: .........*(NumConst=62, SV=11, CEps=3.9284, QPEps=0.1991)
Iter 83: .........*(NumConst=61, SV=13, CEps=3.8731, QPEps=1.9136)
Iter 84: .........*(NumConst=61, SV=11, CEps=4.8998, QPEps=0.0006)
Iter 85: .........*(NumConst=61, SV=12, CEps=3.0982, QPEps=0.4832)
Iter 86: .........*(NumConst=61, SV=14, CEps=5.1889, QPEps=0.3803)
Iter 87: .........*(NumConst=62, SV=15, CEps=3.3603, QPEps=1.0653)
Iter 88: .........*(NumConst=63, SV=14, CEps=2.8159, QPEps=1.0221)
Iter 89: .........*(NumConst=63, SV=13, CEps=4.3125, QPEps=0.6237)
Iter 90: .........*(NumConst=64, SV=14, CEps=3.5101, QPEps=0.2296)
Iter 91: .........*(NumConst=65, SV=14, CEps=2.1148, QPEps=0.6173)
Iter 92: .........*(NumConst=66, SV=14, CEps=2.5451, QPEps=0.8911)
Iter 93: .........*(NumConst=67, SV=13, CEps=2.9123, QPEps=0.5841)
Iter 94: .........*(NumConst=66, SV=12, CEps=3.0804, QPEps=0.4943)
Iter 95: .........*(NumConst=65, SV=13, CEps=1.7478, QPEps=0.3594)
Iter 96: .........*(NumConst=66, SV=13, CEps=1.8056, QPEps=0.5563)
Iter 97: .........*(NumConst=67, SV=13, CEps=1.7803, QPEps=0.1579)
Iter 98: .........*(NumConst=66, SV=13, CEps=1.7866, QPEps=0.8029)
Iter 99: .........*(NumConst=66, SV=15, CEps=1.6122, QPEps=0.6542)
Iter 100: .........*(NumConst=65, SV=14, CEps=1.2855, QPEps=0.4697)
Iter 101: .........*(NumConst=66, SV=14, CEps=1.4040, QPEps=0.1696)
Iter 102: .........*(NumConst=67, SV=14, CEps=1.1436, QPEps=0.5158)
Iter 103: .........(NumConst=67, SV=14, CEps=0.9695, QPEps=0.5158)
Final epsilon on KKT-Conditions: 0.96950
Upper bound on duality gap: 0.44693
Dual objective value: dval=295.51477
Primal objective value: pval=295.96170
Total number of constraints in final working set: 67 (of 102)
Number of iterations: 103
Number of calls to 'find_most_violated_constraint': 18540
Number of SV: 14 
Norm of weight vector: |w|=1.60855
Value of slack variable (on working set): xi=588.88231
Value of slack variable (global): xi=589.33597
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=1217.96110
Runtime in cpu-seconds: 0.40
Compacting linear model...done
Writing learned model...done