Reading training examples...done
Training set properties: 25 features, 180 rankings, 15506 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=0.986667
Iter 1: .........*(NumConst=1, SV=1, CEps=986.6667, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=755.5214, QPEps=0.0002)
Iter 3: .........*(NumConst=3, SV=2, CEps=1317.4938, QPEps=0.0003)
Iter 4: .........*(NumConst=4, SV=3, CEps=1464.1921, QPEps=0.0050)
Iter 5: .........*(NumConst=5, SV=4, CEps=2309.5370, QPEps=0.0334)
Iter 6: .........*(NumConst=6, SV=4, CEps=3359.5114, QPEps=49.5164)
Iter 7: .........*(NumConst=7, SV=5, CEps=1324.6493, QPEps=49.8352)
Iter 8: .........*(NumConst=8, SV=6, CEps=2253.4642, QPEps=0.5073)
Iter 9: .........*(NumConst=9, SV=6, CEps=2335.4430, QPEps=22.6183)
Iter 10: .........*(NumConst=10, SV=7, CEps=575.1155, QPEps=10.3416)
Iter 11: .........*(NumConst=11, SV=10, CEps=477.5819, QPEps=0.0483)
Iter 12: .........*(NumConst=12, SV=9, CEps=436.9940, QPEps=0.0068)
Iter 13: .........*(NumConst=13, SV=8, CEps=471.9697, QPEps=0.0349)
Iter 14: .........*(NumConst=14, SV=9, CEps=279.6074, QPEps=0.0038)
Iter 15: .........*(NumConst=15, SV=9, CEps=262.6497, QPEps=0.0396)
Iter 16: .........*(NumConst=16, SV=9, CEps=480.7502, QPEps=0.0112)
Iter 17: .........*(NumConst=17, SV=9, CEps=416.7363, QPEps=0.0109)
Iter 18: .........*(NumConst=18, SV=8, CEps=270.1813, QPEps=0.0031)
Iter 19: .........*(NumConst=19, SV=9, CEps=161.7898, QPEps=0.0054)
Iter 20: .........*(NumConst=20, SV=9, CEps=216.3028, QPEps=0.0060)
Iter 21: .........*(NumConst=21, SV=9, CEps=221.5962, QPEps=0.0045)
Iter 22: .........*(NumConst=22, SV=9, CEps=222.7658, QPEps=0.0049)
Iter 23: .........*(NumConst=23, SV=8, CEps=118.2167, QPEps=0.0018)
Iter 24: .........*(NumConst=24, SV=10, CEps=214.5105, QPEps=9.3764)
Iter 25: .........*(NumConst=25, SV=9, CEps=148.4699, QPEps=0.0008)
Iter 26: .........*(NumConst=26, SV=9, CEps=104.5618, QPEps=0.0010)
Iter 27: .........*(NumConst=27, SV=9, CEps=114.2553, QPEps=35.7823)
Iter 28: .........*(NumConst=28, SV=9, CEps=130.4159, QPEps=0.0014)
Iter 29: .........*(NumConst=29, SV=9, CEps=97.2331, QPEps=0.0040)
Iter 30: .........*(NumConst=30, SV=9, CEps=115.7250, QPEps=0.0003)
Iter 31: .........*(NumConst=31, SV=10, CEps=84.0859, QPEps=0.0012)
Iter 32: .........*(NumConst=32, SV=10, CEps=82.7229, QPEps=0.0001)
Iter 33: .........*(NumConst=33, SV=10, CEps=80.4159, QPEps=37.1577)
Iter 34: .........*(NumConst=34, SV=11, CEps=131.7360, QPEps=35.5681)
Iter 35: .........*(NumConst=35, SV=11, CEps=56.6961, QPEps=24.9782)
Iter 36: .........*(NumConst=36, SV=11, CEps=75.1959, QPEps=21.4652)
Iter 37: .........*(NumConst=37, SV=11, CEps=72.3609, QPEps=4.9359)
Iter 38: .........*(NumConst=38, SV=14, CEps=51.8834, QPEps=22.8209)
Iter 39: .........*(NumConst=39, SV=11, CEps=67.6616, QPEps=13.3506)
Iter 40: .........*(NumConst=40, SV=10, CEps=49.9033, QPEps=20.9606)
Iter 41: .........*(NumConst=41, SV=10, CEps=54.3911, QPEps=18.8622)
Iter 42: .........*(NumConst=42, SV=11, CEps=93.0125, QPEps=9.5453)
Iter 43: .........*(NumConst=43, SV=10, CEps=38.9920, QPEps=0.0001)
Iter 44: .........*(NumConst=44, SV=11, CEps=39.0100, QPEps=14.1996)
Iter 45: .........*(NumConst=45, SV=12, CEps=57.3509, QPEps=19.4343)
Iter 46: .........*(NumConst=46, SV=12, CEps=32.0502, QPEps=12.4609)
Iter 47: .........*(NumConst=47, SV=11, CEps=28.8473, QPEps=13.9640)
Iter 48: .........*(NumConst=48, SV=13, CEps=29.4412, QPEps=12.3625)
Iter 49: .........*(NumConst=49, SV=13, CEps=41.6518, QPEps=13.4388)
Iter 50: .........*(NumConst=50, SV=12, CEps=33.5580, QPEps=13.2678)
Iter 51: .........*(NumConst=51, SV=12, CEps=31.0116, QPEps=9.4276)
Iter 52: .........*(NumConst=52, SV=12, CEps=25.0430, QPEps=5.0279)
Iter 53: .........*(NumConst=53, SV=13, CEps=14.9098, QPEps=6.7610)
Iter 54: .........*(NumConst=54, SV=13, CEps=24.2175, QPEps=5.0142)
Iter 55: .........*(NumConst=54, SV=12, CEps=25.5031, QPEps=5.1659)
Iter 56: .........*(NumConst=55, SV=11, CEps=17.5577, QPEps=1.7164)
Iter 57: .........*(NumConst=56, SV=11, CEps=15.0991, QPEps=4.2141)
Iter 58: .........*(NumConst=57, SV=10, CEps=13.8964, QPEps=0.0887)
Iter 59: .........*(NumConst=58, SV=11, CEps=21.5473, QPEps=5.9152)
Iter 60: .........*(NumConst=59, SV=12, CEps=13.7834, QPEps=4.1170)
Iter 61: .........*(NumConst=59, SV=13, CEps=17.8987, QPEps=6.4609)
Iter 62: .........*(NumConst=59, SV=11, CEps=16.3181, QPEps=4.5608)
Iter 63: .........*(NumConst=60, SV=10, CEps=17.7434, QPEps=0.0000)
Iter 64: .........*(NumConst=60, SV=10, CEps=8.7429, QPEps=0.0000)
Iter 65: .........*(NumConst=60, SV=9, CEps=10.0852, QPEps=0.2299)
Iter 66: .........*(NumConst=60, SV=10, CEps=6.9888, QPEps=2.7862)
Iter 67: .........*(NumConst=59, SV=10, CEps=19.2765, QPEps=3.0848)
Iter 68: .........*(NumConst=59, SV=13, CEps=6.3708, QPEps=2.8880)
Iter 69: .........*(NumConst=59, SV=11, CEps=11.8199, QPEps=2.7714)
Iter 70: .........*(NumConst=59, SV=12, CEps=8.2827, QPEps=2.3023)
Iter 71: .........*(NumConst=60, SV=11, CEps=11.3444, QPEps=2.6288)
Iter 72: .........*(NumConst=60, SV=10, CEps=6.1780, QPEps=0.8355)
Iter 73: .........*(NumConst=60, SV=11, CEps=7.2938, QPEps=2.5136)
Iter 74: .........*(NumConst=59, SV=12, CEps=9.6026, QPEps=1.2453)
Iter 75: .........*(NumConst=59, SV=11, CEps=5.2771, QPEps=0.3527)
Iter 76: .........*(NumConst=59, SV=13, CEps=3.8932, QPEps=1.5718)
Iter 77: .........*(NumConst=59, SV=12, CEps=6.7497, QPEps=0.2047)
Iter 78: .........*(NumConst=59, SV=11, CEps=4.1557, QPEps=0.5930)
Iter 79: .........*(NumConst=59, SV=13, CEps=3.8761, QPEps=1.3964)
Iter 80: .........*(NumConst=60, SV=11, CEps=3.5603, QPEps=0.8783)
Iter 81: .........*(NumConst=61, SV=12, CEps=4.7127, QPEps=1.2146)
Iter 82: .........*(NumConst=62, SV=12, CEps=3.2004, QPEps=1.5866)
Iter 83: .........*(NumConst=63, SV=12, CEps=5.1430, QPEps=0.7850)
Iter 84: .........*(NumConst=63, SV=11, CEps=3.5574, QPEps=0.5131)
Iter 85: .........*(NumConst=63, SV=11, CEps=1.9049, QPEps=0.0294)
Iter 86: .........*(NumConst=63, SV=11, CEps=2.5996, QPEps=0.3729)
Iter 87: .........*(NumConst=63, SV=11, CEps=3.1770, QPEps=0.7854)
Iter 88: .........*(NumConst=61, SV=10, CEps=1.7226, QPEps=0.5373)
Iter 89: .........*(NumConst=61, SV=13, CEps=2.5991, QPEps=0.7499)
Iter 90: .........*(NumConst=62, SV=12, CEps=3.2725, QPEps=0.1957)
Iter 91: .........*(NumConst=63, SV=13, CEps=2.5761, QPEps=0.4906)
Iter 92: .........*(NumConst=63, SV=13, CEps=1.7368, QPEps=0.3618)
Iter 93: .........*(NumConst=64, SV=14, CEps=1.9285, QPEps=0.6635)
Iter 94: .........*(NumConst=65, SV=12, CEps=2.1344, QPEps=0.4754)
Iter 95: .........*(NumConst=66, SV=12, CEps=2.0855, QPEps=0.3847)
Iter 96: .........*(NumConst=65, SV=11, CEps=1.5099, QPEps=0.3297)
Iter 97: .........*(NumConst=65, SV=12, CEps=1.7500, QPEps=0.4437)
Iter 98: .........*(NumConst=64, SV=14, CEps=1.2426, QPEps=0.3875)
Iter 99: .........*(NumConst=63, SV=13, CEps=1.9834, QPEps=0.5109)
Iter 100: .........(NumConst=63, SV=13, CEps=0.9017, QPEps=0.5109)
Final epsilon on KKT-Conditions: 0.90171
Upper bound on duality gap: 0.42918
Dual objective value: dval=290.50951
Primal objective value: pval=290.93869
Total number of constraints in final working set: 63 (of 99)
Number of iterations: 100
Number of calls to 'find_most_violated_constraint': 18000
Number of SV: 13 
Norm of weight vector: |w|=1.66618
Value of slack variable (on working set): xi=578.71040
Value of slack variable (global): xi=579.10121
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=1269.11803
Runtime in cpu-seconds: 0.91
Compacting linear model...done
Writing learned model...done