Reading training examples...done
Training set properties: 49 features, 90 rankings, 8174 examples
NOTE: Adjusted stopping criterion relative to maximum loss: eps=0.482200
Iter 1: .........*(NumConst=1, SV=1, CEps=482.2000, QPEps=0.0000)
Iter 2: .........*(NumConst=2, SV=2, CEps=1232.4536, QPEps=0.0001)
Iter 3: .........*(NumConst=3, SV=3, CEps=614.1086, QPEps=0.0007)
Iter 4: .........*(NumConst=4, SV=4, CEps=1518.3546, QPEps=0.0014)
Iter 5: .........*(NumConst=5, SV=4, CEps=636.0512, QPEps=0.0014)
Iter 6: .........*(NumConst=6, SV=5, CEps=441.2698, QPEps=0.0016)
Iter 7: .........*(NumConst=7, SV=6, CEps=611.9339, QPEps=0.0078)
Iter 8: .........*(NumConst=8, SV=6, CEps=958.9877, QPEps=6.4754)
Iter 9: .........*(NumConst=9, SV=6, CEps=357.1934, QPEps=3.5873)
Iter 10: .........*(NumConst=10, SV=7, CEps=323.6711, QPEps=24.8264)
Iter 11: .........*(NumConst=11, SV=8, CEps=233.8292, QPEps=22.3868)
Iter 12: .........*(NumConst=12, SV=8, CEps=268.8204, QPEps=25.0415)
Iter 13: .........*(NumConst=13, SV=7, CEps=172.1566, QPEps=6.9378)
Iter 14: .........*(NumConst=14, SV=7, CEps=119.9857, QPEps=0.0055)
Iter 15: .........*(NumConst=15, SV=8, CEps=135.4591, QPEps=0.0171)
Iter 16: .........*(NumConst=16, SV=8, CEps=115.8256, QPEps=0.1555)
Iter 17: .........*(NumConst=17, SV=8, CEps=111.1687, QPEps=0.8659)
Iter 18: .........*(NumConst=18, SV=8, CEps=76.4917, QPEps=13.4181)
Iter 19: .........*(NumConst=19, SV=8, CEps=72.7033, QPEps=9.1565)
Iter 20: .........*(NumConst=20, SV=9, CEps=109.5500, QPEps=34.5529)
Iter 21: .........*(NumConst=21, SV=11, CEps=69.9402, QPEps=29.0835)
Iter 22: .........*(NumConst=22, SV=9, CEps=111.9490, QPEps=21.9990)
Iter 23: .........*(NumConst=23, SV=11, CEps=59.0151, QPEps=0.0003)
Iter 24: .........*(NumConst=24, SV=12, CEps=41.6659, QPEps=0.0003)
Iter 25: .........*(NumConst=25, SV=11, CEps=58.8728, QPEps=0.0003)
Iter 26: .........*(NumConst=26, SV=11, CEps=34.1987, QPEps=6.0707)
Iter 27: .........*(NumConst=27, SV=12, CEps=32.2152, QPEps=12.2940)
Iter 28: .........*(NumConst=28, SV=11, CEps=53.4157, QPEps=0.0002)
Iter 29: .........*(NumConst=29, SV=12, CEps=63.8988, QPEps=2.4112)
Iter 30: .........*(NumConst=30, SV=11, CEps=35.2605, QPEps=0.0001)
Iter 31: .........*(NumConst=31, SV=10, CEps=26.8449, QPEps=0.0009)
Iter 32: .........*(NumConst=32, SV=11, CEps=23.7877, QPEps=5.9676)
Iter 33: .........*(NumConst=33, SV=12, CEps=28.9944, QPEps=9.0427)
Iter 34: .........*(NumConst=34, SV=12, CEps=26.4409, QPEps=7.2754)
Iter 35: .........*(NumConst=35, SV=11, CEps=21.1470, QPEps=0.0001)
Iter 36: .........*(NumConst=36, SV=11, CEps=18.9646, QPEps=0.0000)
Iter 37: .........*(NumConst=37, SV=13, CEps=14.2308, QPEps=5.1796)
Iter 38: .........*(NumConst=38, SV=14, CEps=20.7185, QPEps=0.7096)
Iter 39: .........*(NumConst=39, SV=13, CEps=18.4809, QPEps=4.4231)
Iter 40: .........*(NumConst=40, SV=12, CEps=16.8330, QPEps=0.0000)
Iter 41: .........*(NumConst=41, SV=14, CEps=10.9456, QPEps=4.5279)
Iter 42: .........*(NumConst=42, SV=11, CEps=16.9603, QPEps=0.0000)
Iter 43: .........*(NumConst=43, SV=13, CEps=10.6744, QPEps=2.2051)
Iter 44: .........*(NumConst=44, SV=14, CEps=9.3280, QPEps=2.5518)
Iter 45: .........*(NumConst=45, SV=14, CEps=13.2976, QPEps=4.5700)
Iter 46: .........*(NumConst=46, SV=16, CEps=7.6493, QPEps=2.0196)
Iter 47: .........*(NumConst=47, SV=14, CEps=10.1841, QPEps=1.8269)
Iter 48: .........*(NumConst=48, SV=14, CEps=10.8113, QPEps=3.3883)
Iter 49: .........*(NumConst=49, SV=13, CEps=6.0078, QPEps=2.2251)
Iter 50: .........*(NumConst=50, SV=13, CEps=7.8653, QPEps=1.9927)
Iter 51: .........*(NumConst=51, SV=13, CEps=5.7079, QPEps=0.0000)
Iter 52: .........*(NumConst=52, SV=13, CEps=7.3648, QPEps=0.0001)
Iter 53: .........*(NumConst=53, SV=13, CEps=5.2872, QPEps=0.0001)
Iter 54: .........*(NumConst=54, SV=13, CEps=5.1799, QPEps=1.9525)
Iter 55: .........*(NumConst=55, SV=12, CEps=10.6515, QPEps=0.0001)
Iter 56: .........*(NumConst=56, SV=12, CEps=3.8614, QPEps=1.6987)
Iter 57: .........*(NumConst=56, SV=13, CEps=6.4982, QPEps=1.7696)
Iter 58: .........*(NumConst=57, SV=14, CEps=3.5522, QPEps=0.0000)
Iter 59: .........*(NumConst=57, SV=12, CEps=3.1951, QPEps=0.0001)
Iter 60: .........*(NumConst=58, SV=13, CEps=4.1757, QPEps=0.0000)
Iter 61: .........*(NumConst=59, SV=12, CEps=3.3501, QPEps=1.4182)
Iter 62: .........*(NumConst=58, SV=13, CEps=2.6779, QPEps=0.0000)
Iter 63: .........*(NumConst=58, SV=15, CEps=2.0323, QPEps=0.8368)
Iter 64: .........*(NumConst=59, SV=12, CEps=5.6757, QPEps=0.3068)
Iter 65: .........*(NumConst=60, SV=14, CEps=2.6451, QPEps=0.7965)
Iter 66: .........*(NumConst=61, SV=12, CEps=2.8836, QPEps=0.2880)
Iter 67: .........*(NumConst=60, SV=13, CEps=2.7787, QPEps=0.3640)
Iter 68: .........*(NumConst=60, SV=15, CEps=1.5765, QPEps=0.5217)
Iter 69: .........*(NumConst=60, SV=13, CEps=2.2193, QPEps=0.6391)
Iter 70: .........*(NumConst=60, SV=13, CEps=2.8326, QPEps=0.3212)
Iter 71: .........*(NumConst=59, SV=13, CEps=1.8398, QPEps=0.0000)
Iter 72: .........*(NumConst=60, SV=13, CEps=1.2743, QPEps=0.0006)
Iter 73: .........*(NumConst=61, SV=13, CEps=1.7400, QPEps=0.0005)
Iter 74: .........*(NumConst=60, SV=13, CEps=1.1111, QPEps=0.0002)
Iter 75: .........*(NumConst=60, SV=14, CEps=1.7843, QPEps=0.0297)
Iter 76: .........*(NumConst=61, SV=15, CEps=1.2933, QPEps=0.0978)
Iter 77: .........*(NumConst=61, SV=14, CEps=1.2158, QPEps=0.1070)
Iter 78: .........*(NumConst=62, SV=15, CEps=0.7966, QPEps=0.0000)
Iter 79: .........*(NumConst=62, SV=15, CEps=1.1523, QPEps=0.2903)
Iter 80: .........*(NumConst=62, SV=15, CEps=0.7787, QPEps=0.0000)
Iter 81: .........*(NumConst=62, SV=15, CEps=0.7072, QPEps=0.3502)
Iter 82: .........*(NumConst=63, SV=16, CEps=1.2196, QPEps=0.0000)
Iter 83: .........*(NumConst=63, SV=19, CEps=0.7083, QPEps=0.0986)
Iter 84: .........*(NumConst=62, SV=18, CEps=0.8815, QPEps=0.0000)
Iter 85: .........*(NumConst=62, SV=18, CEps=0.6678, QPEps=0.0019)
Iter 86: .........(NumConst=62, SV=18, CEps=0.4460, QPEps=0.0019)
Final epsilon on KKT-Conditions: 0.44598
Upper bound on duality gap: 0.04471
Dual objective value: dval=25.43925
Primal objective value: pval=25.48395
Total number of constraints in final working set: 62 (of 85)
Number of iterations: 86
Number of calls to 'find_most_violated_constraint': 7740
Number of SV: 18 
Norm of weight vector: |w|=1.86710
Value of slack variable (on working set): xi=236.96318
Value of slack variable (global): xi=237.40916
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=2260.95893
Runtime in cpu-seconds: 0.25
Compacting linear model...done
Writing learned model...done