Reading training examples...done
Training set properties: 23 features, 180 rankings, 15504 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=1.012667
Iter 1: .........*(NumConst=1, SV=1, CEps=1012.6667, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=1040.3239, QPEps=0.0006)
Iter 3: .........*(NumConst=3, SV=3, CEps=2576.0853, QPEps=0.0038)
Iter 4: .........*(NumConst=4, SV=4, CEps=7466.0422, QPEps=0.0057)
Iter 5: .........*(NumConst=5, SV=5, CEps=1153.5845, QPEps=0.0028)
Iter 6: .........*(NumConst=6, SV=5, CEps=2084.3555, QPEps=0.0040)
Iter 7: .........*(NumConst=7, SV=5, CEps=1266.3627, QPEps=49.1856)
Iter 8: .........*(NumConst=8, SV=6, CEps=3065.3548, QPEps=48.0025)
Iter 9: .........*(NumConst=9, SV=6, CEps=5032.1894, QPEps=45.3622)
Iter 10: .........*(NumConst=10, SV=8, CEps=449.1504, QPEps=49.8232)
Iter 11: .........*(NumConst=11, SV=7, CEps=215.6188, QPEps=44.2154)
Iter 12: .........*(NumConst=12, SV=8, CEps=245.0870, QPEps=47.9555)
Iter 13: .........*(NumConst=13, SV=9, CEps=271.5498, QPEps=45.5841)
Iter 14: .........*(NumConst=14, SV=9, CEps=206.5425, QPEps=43.8876)
Iter 15: .........*(NumConst=15, SV=9, CEps=126.6974, QPEps=45.6078)
Iter 16: .........*(NumConst=16, SV=7, CEps=143.3864, QPEps=29.3526)
Iter 17: .........*(NumConst=17, SV=8, CEps=227.3495, QPEps=25.2431)
Iter 18: .........*(NumConst=18, SV=8, CEps=105.5090, QPEps=35.7788)
Iter 19: .........*(NumConst=19, SV=7, CEps=86.1054, QPEps=3.1809)
Iter 20: .........*(NumConst=20, SV=8, CEps=111.2718, QPEps=41.7219)
Iter 21: .........*(NumConst=21, SV=9, CEps=55.9048, QPEps=24.9569)
Iter 22: .........*(NumConst=22, SV=8, CEps=64.3367, QPEps=25.2074)
Iter 23: .........*(NumConst=23, SV=8, CEps=51.4423, QPEps=6.7791)
Iter 24: .........*(NumConst=24, SV=9, CEps=59.2631, QPEps=23.9481)
Iter 25: .........*(NumConst=25, SV=9, CEps=40.6791, QPEps=18.8083)
Iter 26: .........*(NumConst=26, SV=9, CEps=30.4175, QPEps=2.3926)
Iter 27: .........*(NumConst=27, SV=7, CEps=18.5669, QPEps=1.0043)
Iter 28: .........*(NumConst=28, SV=8, CEps=35.2813, QPEps=8.6215)
Iter 29: .........*(NumConst=29, SV=8, CEps=17.7516, QPEps=6.1603)
Iter 30: .........*(NumConst=30, SV=8, CEps=21.8856, QPEps=6.8771)
Iter 31: .........*(NumConst=31, SV=7, CEps=14.5755, QPEps=2.4841)
Iter 32: .........*(NumConst=32, SV=8, CEps=8.4360, QPEps=1.3453)
Iter 33: .........*(NumConst=33, SV=9, CEps=9.2932, QPEps=2.5378)
Iter 34: .........*(NumConst=34, SV=9, CEps=15.5546, QPEps=3.8405)
Iter 35: .........*(NumConst=35, SV=10, CEps=5.8173, QPEps=2.3854)
Iter 36: .........*(NumConst=36, SV=8, CEps=11.0293, QPEps=2.4651)
Iter 37: .........*(NumConst=37, SV=8, CEps=4.3362, QPEps=0.6913)
Iter 38: .........*(NumConst=38, SV=8, CEps=13.4222, QPEps=1.8227)
Iter 39: .........*(NumConst=39, SV=7, CEps=4.7579, QPEps=0.4051)
Iter 40: .........*(NumConst=40, SV=10, CEps=2.9484, QPEps=1.0907)
Iter 41: .........*(NumConst=41, SV=10, CEps=4.9901, QPEps=1.4213)
Iter 42: .........*(NumConst=42, SV=9, CEps=4.1977, QPEps=0.9788)
Iter 43: .........*(NumConst=43, SV=8, CEps=2.6185, QPEps=1.0844)
Iter 44: .........*(NumConst=44, SV=10, CEps=1.8363, QPEps=0.7334)
Iter 45: .........*(NumConst=45, SV=8, CEps=2.3027, QPEps=0.2115)
Iter 46: .........*(NumConst=46, SV=9, CEps=1.9143, QPEps=0.0198)
Iter 47: .........(NumConst=46, SV=9, CEps=0.8360, QPEps=0.0198)
Final epsilon on KKT-Conditions: 0.83604
Upper bound on duality gap: 0.08337
Dual objective value: dval=65.40683
Primal objective value: pval=65.49020
Total number of constraints in final working set: 46 (of 46)
Number of iterations: 47
Number of calls to 'find_most_violated_constraint': 8460
Number of SV: 9 
Norm of weight vector: |w|=1.39564
Value of slack variable (on working set): xi=644.34666
Value of slack variable (global): xi=645.16300
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=5483.67968
Runtime in cpu-seconds: 2.41
Compacting linear model...done
Writing learned model...done