Reading training examples...done
Training set properties: 19 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=470.5587, QPEps=0.0004)
Iter 3: .........*(NumConst=3, SV=3, CEps=829.1378, QPEps=0.0041)
Iter 4: .........*(NumConst=4, SV=3, CEps=601.3748, QPEps=0.0004)
Iter 5: .........*(NumConst=5, SV=4, CEps=346.9424, QPEps=0.0003)
Iter 6: .........*(NumConst=6, SV=5, CEps=1488.2345, QPEps=0.0017)
Iter 7: .........*(NumConst=7, SV=6, CEps=597.6536, QPEps=0.0115)
Iter 8: .........*(NumConst=8, SV=6, CEps=199.6114, QPEps=23.8703)
Iter 9: .........*(NumConst=9, SV=6, CEps=132.6536, QPEps=41.2118)
Iter 10: .........*(NumConst=10, SV=7, CEps=117.4576, QPEps=43.6789)
Iter 11: .........*(NumConst=11, SV=9, CEps=72.3388, QPEps=19.1010)
Iter 12: .........*(NumConst=12, SV=8, CEps=158.4283, QPEps=33.2349)
Iter 13: .........*(NumConst=13, SV=8, CEps=98.0033, QPEps=34.8616)
Iter 14: .........*(NumConst=14, SV=8, CEps=63.8160, QPEps=1.1592)
Iter 15: .........*(NumConst=15, SV=8, CEps=96.1389, QPEps=0.0250)
Iter 16: .........*(NumConst=16, SV=7, CEps=49.1623, QPEps=12.9798)
Iter 17: .........*(NumConst=17, SV=8, CEps=57.3951, QPEps=24.3796)
Iter 18: .........*(NumConst=18, SV=8, CEps=42.9737, QPEps=21.4080)
Iter 19: .........*(NumConst=19, SV=10, CEps=47.8793, QPEps=13.9597)
Iter 20: .........*(NumConst=20, SV=10, CEps=81.7512, QPEps=0.0047)
Iter 21: .........*(NumConst=21, SV=10, CEps=40.1283, QPEps=19.5203)
Iter 22: .........*(NumConst=22, SV=9, CEps=38.6707, QPEps=17.1553)
Iter 23: .........*(NumConst=23, SV=9, CEps=28.6915, QPEps=1.5499)
Iter 24: .........*(NumConst=24, SV=8, CEps=17.5186, QPEps=1.0497)
Iter 25: .........*(NumConst=25, SV=9, CEps=20.2419, QPEps=2.5455)
Iter 26: .........*(NumConst=26, SV=9, CEps=12.3060, QPEps=3.9960)
Iter 27: .........*(NumConst=27, SV=9, CEps=33.8880, QPEps=2.4073)
Iter 28: .........*(NumConst=28, SV=9, CEps=16.7879, QPEps=2.8919)
Iter 29: .........*(NumConst=29, SV=8, CEps=13.9142, QPEps=5.8016)
Iter 30: .........*(NumConst=30, SV=9, CEps=11.2161, QPEps=0.0002)
Iter 31: .........*(NumConst=31, SV=9, CEps=14.8284, QPEps=5.5410)
Iter 32: .........*(NumConst=32, SV=9, CEps=9.1750, QPEps=4.0092)
Iter 33: .........*(NumConst=33, SV=8, CEps=5.8072, QPEps=2.7308)
Iter 34: .........*(NumConst=34, SV=8, CEps=5.1659, QPEps=1.4072)
Iter 35: .........*(NumConst=35, SV=9, CEps=3.7776, QPEps=0.0013)
Iter 36: .........*(NumConst=36, SV=9, CEps=8.1142, QPEps=0.5563)
Iter 37: .........*(NumConst=37, SV=9, CEps=3.7830, QPEps=0.2356)
Iter 38: .........*(NumConst=38, SV=10, CEps=3.6895, QPEps=0.0027)
Iter 39: .........*(NumConst=39, SV=10, CEps=3.6074, QPEps=0.0005)
Iter 40: .........*(NumConst=40, SV=10, CEps=2.1020, QPEps=0.6698)
Iter 41: .........*(NumConst=41, SV=10, CEps=2.0395, QPEps=0.9006)
Iter 42: .........*(NumConst=42, SV=10, CEps=1.7667, QPEps=0.0337)
Iter 43: .........*(NumConst=43, SV=10, CEps=2.0323, QPEps=0.6854)
Iter 44: .........*(NumConst=44, SV=9, CEps=1.5373, QPEps=0.7521)
Iter 45: .........*(NumConst=45, SV=9, CEps=1.3405, QPEps=0.6255)
Iter 46: .........*(NumConst=46, SV=9, CEps=1.0013, QPEps=0.2298)
Iter 47: .........*(NumConst=47, SV=9, CEps=1.9161, QPEps=0.0038)
Iter 48: .........*(NumConst=48, SV=9, CEps=0.8256, QPEps=0.2431)
Iter 49: .........*(NumConst=49, SV=8, CEps=0.6826, QPEps=0.2823)
Iter 50: .........*(NumConst=50, SV=8, CEps=0.6311, QPEps=0.3031)
Iter 51: .........(NumConst=50, SV=8, CEps=0.3940, QPEps=0.3031)
Final epsilon on KKT-Conditions: 0.39402
Upper bound on duality gap: 0.03074
Dual objective value: dval=29.17825
Primal objective value: pval=29.20898
Total number of constraints in final working set: 50 (of 50)
Number of iterations: 51
Number of calls to 'find_most_violated_constraint': 4590
Number of SV: 8 
Norm of weight vector: |w|=1.89084
Value of slack variable (on working set): xi=274.11720
Value of slack variable (global): xi=274.21345
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=2650.36562
Runtime in cpu-seconds: 0.36
Compacting linear model...done
Writing learned model...done