Reading training examples...done
Training set properties: 49 features, 180 rankings, 15573 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=0.987111
Iter 1: .........*(NumConst=1, SV=1, CEps=987.1111, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=1523.4256, QPEps=0.0002)
Iter 3: .........*(NumConst=3, SV=3, CEps=1610.3077, QPEps=0.0005)
Iter 4: .........*(NumConst=4, SV=4, CEps=1511.2066, QPEps=0.0122)
Iter 5: .........*(NumConst=5, SV=4, CEps=1366.6127, QPEps=0.0011)
Iter 6: .........*(NumConst=6, SV=5, CEps=1206.3503, QPEps=0.0097)
Iter 7: .........*(NumConst=7, SV=5, CEps=1582.6844, QPEps=15.7813)
Iter 8: .........*(NumConst=8, SV=6, CEps=965.6674, QPEps=49.4190)
Iter 9: .........*(NumConst=9, SV=8, CEps=628.2092, QPEps=0.0166)
Iter 10: .........*(NumConst=10, SV=8, CEps=472.1417, QPEps=5.9090)
Iter 11: .........*(NumConst=11, SV=8, CEps=328.1327, QPEps=43.4130)
Iter 12: .........*(NumConst=12, SV=7, CEps=250.9582, QPEps=20.3819)
Iter 13: .........*(NumConst=13, SV=7, CEps=218.8219, QPEps=3.3463)
Iter 14: .........*(NumConst=14, SV=7, CEps=190.3336, QPEps=0.0212)
Iter 15: .........*(NumConst=15, SV=8, CEps=228.2377, QPEps=0.4193)
Iter 16: .........*(NumConst=16, SV=7, CEps=220.0882, QPEps=8.0616)
Iter 17: .........*(NumConst=17, SV=8, CEps=161.3092, QPEps=0.0272)
Iter 18: .........*(NumConst=18, SV=7, CEps=141.5205, QPEps=6.7709)
Iter 19: .........*(NumConst=19, SV=8, CEps=105.4841, QPEps=4.8536)
Iter 20: .........*(NumConst=20, SV=8, CEps=96.5158, QPEps=0.0008)
Iter 21: .........*(NumConst=21, SV=8, CEps=70.7039, QPEps=10.3070)
Iter 22: .........*(NumConst=22, SV=8, CEps=85.2880, QPEps=25.8937)
Iter 23: .........*(NumConst=23, SV=8, CEps=114.6429, QPEps=0.0035)
Iter 24: .........*(NumConst=24, SV=9, CEps=74.5400, QPEps=33.0343)
Iter 25: .........*(NumConst=25, SV=8, CEps=53.2289, QPEps=26.4254)
Iter 26: .........*(NumConst=26, SV=9, CEps=77.5993, QPEps=4.4681)
Iter 27: .........*(NumConst=27, SV=9, CEps=60.6393, QPEps=9.9879)
Iter 28: .........*(NumConst=28, SV=9, CEps=74.7347, QPEps=0.0585)
Iter 29: .........*(NumConst=29, SV=9, CEps=36.1102, QPEps=0.0006)
Iter 30: .........*(NumConst=30, SV=9, CEps=66.5990, QPEps=8.8157)
Iter 31: .........*(NumConst=31, SV=9, CEps=52.5820, QPEps=10.2185)
Iter 32: .........*(NumConst=32, SV=10, CEps=51.3826, QPEps=16.1958)
Iter 33: .........*(NumConst=33, SV=9, CEps=27.1791, QPEps=5.1152)
Iter 34: .........*(NumConst=34, SV=8, CEps=38.6389, QPEps=0.0023)
Iter 35: .........*(NumConst=35, SV=8, CEps=28.4986, QPEps=0.0001)
Iter 36: .........*(NumConst=36, SV=8, CEps=31.5449, QPEps=0.0022)
Iter 37: .........*(NumConst=37, SV=8, CEps=19.2393, QPEps=0.0024)
Iter 38: .........*(NumConst=38, SV=10, CEps=22.7991, QPEps=0.0001)
Iter 39: .........*(NumConst=39, SV=9, CEps=23.7101, QPEps=0.0003)
Iter 40: .........*(NumConst=40, SV=8, CEps=19.8987, QPEps=0.0001)
Iter 41: .........*(NumConst=41, SV=8, CEps=14.6805, QPEps=0.0076)
Iter 42: .........*(NumConst=42, SV=8, CEps=13.7619, QPEps=0.1298)
Iter 43: .........*(NumConst=43, SV=9, CEps=11.0508, QPEps=2.4774)
Iter 44: .........*(NumConst=44, SV=8, CEps=20.8078, QPEps=0.0344)
Iter 45: .........*(NumConst=45, SV=8, CEps=13.5407, QPEps=0.7375)
Iter 46: .........*(NumConst=46, SV=8, CEps=10.3649, QPEps=1.2277)
Iter 47: .........*(NumConst=47, SV=8, CEps=10.5326, QPEps=0.0129)
Iter 48: .........*(NumConst=48, SV=9, CEps=6.4448, QPEps=1.2647)
Iter 49: .........*(NumConst=49, SV=9, CEps=13.1227, QPEps=1.6650)
Iter 50: .........*(NumConst=50, SV=10, CEps=10.1783, QPEps=0.0000)
Iter 51: .........*(NumConst=51, SV=10, CEps=6.0372, QPEps=1.7324)
Iter 52: .........*(NumConst=52, SV=8, CEps=8.6068, QPEps=0.0018)
Iter 53: .........*(NumConst=53, SV=9, CEps=7.5042, QPEps=0.0900)
Iter 54: .........*(NumConst=54, SV=9, CEps=4.5233, QPEps=1.0217)
Iter 55: .........*(NumConst=55, SV=9, CEps=5.3954, QPEps=0.0006)
Iter 56: .........*(NumConst=56, SV=8, CEps=5.3238, QPEps=0.0008)
Iter 57: .........*(NumConst=57, SV=9, CEps=3.5747, QPEps=0.0010)
Iter 58: .........*(NumConst=58, SV=9, CEps=3.9151, QPEps=0.0120)
Iter 59: .........*(NumConst=58, SV=10, CEps=2.8485, QPEps=0.2328)
Iter 60: .........*(NumConst=58, SV=11, CEps=6.9299, QPEps=0.8486)
Iter 61: .........*(NumConst=57, SV=12, CEps=3.3890, QPEps=0.4065)
Iter 62: .........*(NumConst=57, SV=11, CEps=3.8491, QPEps=0.6196)
Iter 63: .........*(NumConst=57, SV=10, CEps=3.9843, QPEps=1.3870)
Iter 64: .........*(NumConst=57, SV=14, CEps=1.7872, QPEps=0.7120)
Iter 65: .........*(NumConst=56, SV=10, CEps=4.9459, QPEps=0.0021)
Iter 66: .........*(NumConst=57, SV=9, CEps=2.9984, QPEps=0.0000)
Iter 67: .........*(NumConst=56, SV=8, CEps=1.9880, QPEps=0.0532)
Iter 68: .........*(NumConst=57, SV=8, CEps=2.3230, QPEps=0.0001)
Iter 69: .........*(NumConst=57, SV=8, CEps=1.8891, QPEps=0.0018)
Iter 70: .........*(NumConst=57, SV=10, CEps=1.1044, QPEps=0.0000)
Iter 71: .........*(NumConst=57, SV=9, CEps=1.8492, QPEps=0.0003)
Iter 72: .........*(NumConst=58, SV=9, CEps=1.1733, QPEps=0.5312)
Iter 73: .........*(NumConst=59, SV=8, CEps=1.3539, QPEps=0.4695)
Iter 74: .........*(NumConst=57, SV=8, CEps=0.9965, QPEps=0.1417)
Iter 75: .........(NumConst=57, SV=8, CEps=0.6287, QPEps=0.1417)
Final epsilon on KKT-Conditions: 0.62873
Upper bound on duality gap: 0.02108
Dual objective value: dval=17.68371
Primal objective value: pval=17.70478
Total number of constraints in final working set: 57 (of 74)
Number of iterations: 75
Number of calls to 'find_most_violated_constraint': 13500
Number of SV: 8 
Norm of weight vector: |w|=1.26973
Value of slack variable (on working set): xi=562.66045
Value of slack variable (global): xi=563.28919
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=3728.92852
Runtime in cpu-seconds: 0.48
Compacting linear model...done
Writing learned model...done