{"id":528,"date":"2021-03-18T11:44:12","date_gmt":"2021-03-18T15:44:12","guid":{"rendered":"https:\/\/people.clas.ufl.edu\/hager\/?page_id=528"},"modified":"2026-03-19T08:18:24","modified_gmt":"2026-03-19T12:18:24","slug":"runfile-for-gpdt","status":"publish","type":"page","link":"https:\/\/people.clas.ufl.edu\/hager\/runfile-for-gpdt\/","title":{"rendered":"Runfile for GPDT"},"content":{"rendered":"\r\n
\r\n\t
\r\n\t\t
\r\n\t\t\t
\r\n\t\t\t\t\n

Runfile for GPDT<\/h1>\n\n\n\n

——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 120
\n– Total CPU time: 6.350000
\n– Total kernel evaluations: 2041911
\n– Total inner solver iterations: 62345
\n– Total projector iterations: 316587
\n– Total preparation time: 0.300000
\n– Total inner solver time: 5.500000
\n– Total gradient updating time: 0.210000
\n– Objective function value: -5699.250660
\n– SV = 5766
\n– BSV = 5650
\n– Threshold b = 1.7789981<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 170
\n– Total CPU time: 52.230000
\n– Total kernel evaluations: 2889583
\n– Total inner solver iterations: 564386
\n– Total projector iterations: 2678827
\n– Total preparation time: 0.410000
\n– Total inner solver time: 51.090000
\n– Total gradient updating time: 0.340000
\n– Objective function value: -56875.578661
\n– SV = 5757
\n– BSV = 5629
\n– Threshold b = 1.802115<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 250
\n\tn: 82
\n\tC: 10.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 217
\n– Total CPU time: 400.890000
\n– Total kernel evaluations: 3714292
\n– Total inner solver iterations: 4428660
\n– Total projector iterations: 20036784
\n– Total preparation time: 0.560000
\n– Total inner solver time: 399.360000
\n– Total gradient updating time: 0.410000
\n– Objective function value: -568626.882866
\n– SV = 5755
\n– BSV = 5631
\n– Threshold b = 1.8024634<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 250
\n\tn: 82
\n\tC: 100.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 229
\n– Total CPU time: 3679.050000
\n– Total kernel evaluations: 3936029
\n– Total inner solver iterations: 40736826
\n– Total projector iterations: 182584938
\n– Total preparation time: 0.500000
\n– Total inner solver time: 3677.400000
\n– Total gradient updating time: 0.530000
\n– Objective function value: -5686141.091968
\n– SV = 5758
\n– BSV = 5631
\n– Threshold b = 1.8080527<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1000.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 53
\n– Total CPU time: 21.520000
\n– Total kernel evaluations: 121906520
\n– Total inner solver iterations: 2550
\n– Total projector iterations: 14439
\n– Total preparation time: 0.590000
\n– Total inner solver time: 0.420000
\n– Total gradient updating time: 20.370000
\n– Objective function value: -5899.070838
\n– SV = 6175
\n– BSV = 6053
\n– Threshold b = 0.53433475<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081967213
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 55
\n– Total CPU time: 24.090000
\n– Total kernel evaluations: 124841766
\n– Total inner solver iterations: 9704
\n– Total projector iterations: 40215
\n– Total preparation time: 0.600000
\n– Total inner solver time: 2.250000
\n– Total gradient updating time: 21.090000
\n– Objective function value: -55195.294140
\n– SV = 5835
\n– BSV = 5535
\n– Threshold b = -0.22797893<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081967213
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 91
\n– Total CPU time: 49.650000
\n– Total kernel evaluations: 171010636
\n– Total inner solver iterations: 52908
\n– Total projector iterations: 195602
\n– Total preparation time: 0.850000
\n– Total inner solver time: 18.530000
\n– Total gradient updating time: 29.960000
\n– Objective function value: -506954.068298
\n– SV = 5771
\n– BSV = 4911
\n– Threshold b = -1.1401316<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081967213
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance temporary changed to: 1.000000e-04
\nInner tolerance temporary changed to: 1.000000e-04
\nInner tolerance temporary changed to: 1.000000e-04
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 561
\n– Total CPU time: 402.530000
\n– Total kernel evaluations: 1069707769
\n– Total inner solver iterations: 392673
\n– Total projector iterations: 1215094
\n– Total preparation time: 5.460000
\n– Total inner solver time: 206.320000
\n– Total gradient updating time: 189.140000
\n– Objective function value: -4380314.030831
\n– SV = 5891
\n– BSV = 3957
\n– Threshold b = -2.4793246<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081967213
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 59
\n– Total CPU time: 20.770000
\n– Total kernel evaluations: 143436975
\n– Total inner solver iterations: 895
\n– Total projector iterations: 9553
\n– Total preparation time: 0.510000
\n– Total inner solver time: 0.240000
\n– Total gradient updating time: 19.890000
\n– Objective function value: -7720.477821
\n– SV = 7892
\n– BSV = 7790
\n– Threshold b = 0.98192327<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081967213
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 57
\n– Total CPU time: 20.110000
\n– Total kernel evaluations: 139271437
\n– Total inner solver iterations: 1349
\n– Total projector iterations: 10236
\n– Total preparation time: 0.430000
\n– Total inner solver time: 0.380000
\n– Total gradient updating time: 19.140000
\n– Objective function value: -67778.168723
\n– SV = 7564
\n– BSV = 7389
\n– Threshold b = 0.87140544<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081967213
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 56
\n– Total CPU time: 19.340000
\n– Total kernel evaluations: 129527528
\n– Total inner solver iterations: 2632
\n– Total projector iterations: 12783
\n– Total preparation time: 0.470000
\n– Total inner solver time: 0.690000
\n– Total gradient updating time: 18.060000
\n– Objective function value: -569368.247924
\n– SV = 6318
\n– BSV = 5794
\n– Threshold b = 0.83732077<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081967213
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 94
\n– Total CPU time: 34.620000
\n– Total kernel evaluations: 209344201
\n– Total inner solver iterations: 8573
\n– Total projector iterations: 29402
\n– Total preparation time: 0.800000
\n– Total inner solver time: 3.470000
\n– Total gradient updating time: 30.110000
\n– Objective function value: -4897076.256008
\n– SV = 6091
\n– BSV = 4692
\n– Threshold b = 0.81599513<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a7a
\n\tNumber of training documents: 16100
\n\tModel file: datasets\/a7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081967213
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 171
\n– Total CPU time: 10.650000
\n– Total kernel evaluations: 2932064
\n– Total inner solver iterations: 98318
\n– Total projector iterations: 492731
\n– Total preparation time: 0.450000
\n– Total inner solver time: 9.090000
\n– Total gradient updating time: 0.430000
\n– Objective function value: -8062.407097
\n– SV = 8141
\n– BSV = 8009
\n– Threshold b = 1.6110296<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 259
\n– Total CPU time: 80.830000
\n– Total kernel evaluations: 4460260
\n– Total inner solver iterations: 846762
\n– Total projector iterations: 3825903
\n– Total preparation time: 0.600000
\n– Total inner solver time: 78.480000
\n– Total gradient updating time: 0.670000
\n– Objective function value: -80514.292246
\n– SV = 8133
\n– BSV = 7968
\n– Threshold b = 1.6744623<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 250
\n\tn: 82
\n\tC: 10.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 340
\n– Total CPU time: 649.740000
\n– Total kernel evaluations: 5860115
\n– Total inner solver iterations: 6989174
\n– Total projector iterations: 30300330
\n– Total preparation time: 0.860000
\n– Total inner solver time: 646.680000
\n– Total gradient updating time: 0.970000
\n– Objective function value: -805020.867146
\n– SV = 8131
\n– BSV = 7979
\n– Threshold b = 1.6814698<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 250
\n\tn: 82
\n\tC: 100.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nDai-Fletcher method exits after maxvpm = 3000000 iterations.<\/p>\n\n\n\n\n\n

Dai-Fletcher method exits after maxvpm = 3000000 iterations.<\/p>\n\n\n\n\n\n

——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 366
\n– Total CPU time: 6022.270000
\n– Total kernel evaluations: 6324443
\n– Total inner solver iterations: 66502476
\n– Total projector iterations: 281461347
\n– Total preparation time: 0.860000
\n– Total inner solver time: 6018.950000
\n– Total gradient updating time: 1.100000
\n– Objective function value: -8050084.533977
\n– SV = 8129
\n– BSV = 7968
\n– Threshold b = 1.6843124<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1000.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 73
\n– Total CPU time: 44.010000
\n– Total kernel evaluations: 240357338
\n– Total inner solver iterations: 3485
\n– Total projector iterations: 19404
\n– Total preparation time: 0.840000
\n– Total inner solver time: 0.530000
\n– Total gradient updating time: 42.380000
\n– Objective function value: -8249.503968
\n– SV = 8557
\n– BSV = 8436
\n– Threshold b = 0.48334343<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081300813
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 78
\n– Total CPU time: 48.650000
\n– Total kernel evaluations: 248223033
\n– Total inner solver iterations: 14848
\n– Total projector iterations: 59660
\n– Total preparation time: 0.880000
\n– Total inner solver time: 3.660000
\n– Total gradient updating time: 43.830000
\n– Objective function value: -77831.158453
\n– SV = 8207
\n– BSV = 7790
\n– Threshold b = -0.046799462<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081300813
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 155
\n– Total CPU time: 121.290000
\n– Total kernel evaluations: 484205762
\n– Total inner solver iterations: 85245
\n– Total projector iterations: 278172
\n– Total preparation time: 1.690000
\n– Total inner solver time: 29.780000
\n– Total gradient updating time: 89.180000
\n– Objective function value: -722408.552590
\n– SV = 8070
\n– BSV = 6984
\n– Threshold b = -0.013488531<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081300813
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance temporary changed to: 1.000000e-04
\nInner tolerance changed to: 0.000500
\nInner tolerance changed to: 0.000250
\nInner tolerance changed to: 0.000125
\nInner tolerance changed to: 0.000100
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 1074
\n– Total CPU time: 874.340000
\n– Total kernel evaluations: 3017041934
\n– Total inner solver iterations: 661037
\n– Total projector iterations: 1914110
\n– Total preparation time: 11.050000
\n– Total inner solver time: 294.100000
\n– Total gradient updating time: 564.820000
\n– Objective function value: -6393677.305006
\n– SV = 8224
\n– BSV = 5847
\n– Threshold b = -0.92830709<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081300813
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 83
\n– Total CPU time: 42.670000
\n– Total kernel evaluations: 280174346
\n– Total inner solver iterations: 1153
\n– Total projector iterations: 12258
\n– Total preparation time: 0.760000
\n– Total inner solver time: 0.350000
\n– Total gradient updating time: 41.300000
\n– Objective function value: -10797.570783
\n– SV = 11092
\n– BSV = 10942
\n– Threshold b = 0.97466918<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081300813
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 78
\n– Total CPU time: 40.740000
\n– Total kernel evaluations: 267677742
\n– Total inner solver iterations: 1963
\n– Total projector iterations: 14427
\n– Total preparation time: 0.720000
\n– Total inner solver time: 0.450000
\n– Total gradient updating time: 39.270000
\n– Objective function value: -92870.588420
\n– SV = 10263
\n– BSV = 10039
\n– Threshold b = 0.85743449<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081300813
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 77
\n– Total CPU time: 40.420000
\n– Total kernel evaluations: 260631906
\n– Total inner solver iterations: 3701
\n– Total projector iterations: 17980
\n– Total preparation time: 0.650000
\n– Total inner solver time: 1.000000
\n– Total gradient updating time: 38.480000
\n– Objective function value: -796649.407910
\n– SV = 8730
\n– BSV = 8074
\n– Threshold b = 0.81591892<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081300813
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 151
\n– Total CPU time: 84.090000
\n– Total kernel evaluations: 505154267
\n– Total inner solver iterations: 13269
\n– Total projector iterations: 45016
\n– Total preparation time: 1.280000
\n– Total inner solver time: 5.680000
\n– Total gradient updating time: 76.610000
\n– Objective function value: -6986202.669529
\n– SV = 8489
\n– BSV = 6633
\n– Threshold b = 0.76558633<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a8a
\n\tNumber of training documents: 22696
\n\tModel file: datasets\/a8a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081300813
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 257
\n– Total CPU time: 17.650000
\n– Total kernel evaluations: 4446527
\n– Total inner solver iterations: 151407
\n– Total projector iterations: 732696
\n– Total preparation time: 0.720000
\n– Total inner solver time: 14.250000
\n– Total gradient updating time: 1.250000
\n– Objective function value: -11433.386942
\n– SV = 11546
\n– BSV = 11318
\n– Threshold b = 1.5692328<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 423
\n– Total CPU time: 129.940000
\n– Total kernel evaluations: 7311537
\n– Total inner solver iterations: 1344293
\n– Total projector iterations: 5980805
\n– Total preparation time: 1.060000
\n– Total inner solver time: 124.470000
\n– Total gradient updating time: 1.920000
\n– Objective function value: -114237.471650
\n– SV = 11537
\n– BSV = 11354
\n– Threshold b = 1.6150414<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 250
\n\tn: 82
\n\tC: 10.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 546
\n– Total CPU time: 1009.960000
\n– Total kernel evaluations: 9445250
\n– Total inner solver iterations: 10889677
\n– Total projector iterations: 47457845
\n– Total preparation time: 1.570000
\n– Total inner solver time: 1002.760000
\n– Total gradient updating time: 2.730000
\n– Objective function value: -1142270.677400
\n– SV = 11507
\n– BSV = 11343
\n– Threshold b = 1.622076<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 250
\n\tn: 82
\n\tC: 100.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nDai-Fletcher method exits after maxvpm = 3000000 iterations.<\/p>\n\n\n\n\n\n

Dai-Fletcher method exits after maxvpm = 3000000 iterations.<\/p>\n\n\n\n\n\n

——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 619
\n– Total CPU time: 9951.950000
\n– Total kernel evaluations: 10552620
\n– Total inner solver iterations: 107291991
\n– Total projector iterations: 443813262
\n– Total preparation time: 1.690000
\n– Total inner solver time: 9943.820000
\n– Total gradient updating time: 3.030000
\n– Objective function value: -11422601.171523
\n– SV = 11511
\n– BSV = 11331
\n– Threshold b = 1.6248048<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1000.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 102
\n– Total CPU time: 112.790000
\n– Total kernel evaluations: 498514356
\n– Total inner solver iterations: 5442
\n– Total projector iterations: 30243
\n– Total preparation time: 1.360000
\n– Total inner solver time: 1.070000
\n– Total gradient updating time: 109.790000
\n– Objective function value: -11596.355118
\n– SV = 12019
\n– BSV = 11810
\n– Threshold b = 0.38899895<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081300813
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 113
\n– Total CPU time: 135.810000
\n– Total kernel evaluations: 573563075
\n– Total inner solver iterations: 21391
\n– Total projector iterations: 83260
\n– Total preparation time: 1.540000
\n– Total inner solver time: 6.470000
\n– Total gradient updating time: 127.180000
\n– Objective function value: -110168.548905
\n– SV = 11586
\n– BSV = 11000
\n– Threshold b = 0.088085313<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081300813
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 251
\n– Total CPU time: 425.620000
\n– Total kernel evaluations: 1637924255
\n– Total inner solver iterations: 136677
\n– Total projector iterations: 469149
\n– Total preparation time: 3.320000
\n– Total inner solver time: 55.420000
\n– Total gradient updating time: 365.490000
\n– Objective function value: -1036083.049439
\n– SV = 11466
\n– BSV = 9997
\n– Threshold b = 0.22649909<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081300813
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance temporary changed to: 1.000000e-04
\nInner tolerance changed to: 0.000500
\nInner tolerance changed to: 0.000250
\nInner tolerance changed to: 0.000125
\nInner tolerance changed to: 0.000100
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 2198
\n– Total CPU time: 4584.310000
\n– Total kernel evaluations: 15599983086
\n– Total inner solver iterations: 1194930
\n– Total projector iterations: 3388398
\n– Total preparation time: 29.960000
\n– Total inner solver time: 598.060000
\n– Total gradient updating time: 3942.270000
\n– Objective function value: -9390000.025150
\n– SV = 11759
\n– BSV = 8573
\n– Threshold b = -1.6160973<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0081300813
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 119
\n– Total CPU time: 149.240000
\n– Total kernel evaluations: 662645620
\n– Total inner solver iterations: 1677
\n– Total projector iterations: 17497
\n– Total preparation time: 1.380000
\n– Total inner solver time: 0.430000
\n– Total gradient updating time: 146.680000
\n– Objective function value: -15243.504083
\n– SV = 15758
\n– BSV = 15615
\n– Threshold b = 0.96304967<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081300813
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 107
\n– Total CPU time: 127.860000
\n– Total kernel evaluations: 572554122
\n– Total inner solver iterations: 2558
\n– Total projector iterations: 18088
\n– Total preparation time: 1.250000
\n– Total inner solver time: 0.640000
\n– Total gradient updating time: 125.280000
\n– Objective function value: -128316.403498
\n– SV = 14034
\n– BSV = 13717
\n– Threshold b = 0.84409737<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081300813
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 110
\n– Total CPU time: 133.150000
\n– Total kernel evaluations: 631458412
\n– Total inner solver iterations: 6007
\n– Total projector iterations: 28104
\n– Total preparation time: 1.240000
\n– Total inner solver time: 2.400000
\n– Total gradient updating time: 128.930000
\n– Objective function value: -1119764.274369
\n– SV = 12185
\n– BSV = 11305
\n– Threshold b = 0.82704188<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081300813
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000<\/p>\n\n\n\n\n\n

——+———–+———–+————-+———–+————–
\nInner tolerance changed to: 0.000500
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 290
\n– Total CPU time: 413.620000
\n– Total kernel evaluations: 2096220607
\n– Total inner solver iterations: 23843
\n– Total projector iterations: 80453
\n– Total preparation time: 3.010000
\n– Total inner solver time: 9.480000
\n– Total gradient updating time: 399.250000
\n– Objective function value: -10003494.125343
\n– SV = 12039
\n– BSV = 9419
\n– Threshold b = 0.78621716<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/a9a
\n\tNumber of training documents: 32561
\n\tModel file: datasets\/a9a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0081300813
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000<\/p>\n\n\n\n\n\n

——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 201
\n– Total CPU time: 7.330000
\n– Total kernel evaluations: 3431346
\n– Total inner solver iterations: 60184
\n– Total projector iterations: 347967
\n– Total preparation time: 0.480000
\n– Total inner solver time: 3.740000
\n– Total gradient updating time: 1.390000
\n– Objective function value: -8590.157121
\n– SV = 8667
\n– BSV = 8619
\n– Threshold b = 1.0852663<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 250
\n\tn: 82
\n\tC: 1.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 252
\n– Total CPU time: 27.080000
\n– Total kernel evaluations: 4336511
\n– Total inner solver iterations: 375250
\n– Total projector iterations: 1954816
\n– Total preparation time: 0.570000
\n– Total inner solver time: 22.530000
\n– Total gradient updating time: 1.790000
\n– Objective function value: -85440.979634
\n– SV = 8569
\n– BSV = 8532
\n– Threshold b = 1.0682535<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 250
\n\tn: 82
\n\tC: 10.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 322
\n– Total CPU time: 185.360000
\n– Total kernel evaluations: 5503105
\n– Total inner solver iterations: 2968763
\n– Total projector iterations: 14726362
\n– Total preparation time: 0.790000
\n– Total inner solver time: 179.650000
\n– Total gradient updating time: 2.150000
\n– Objective function value: -853925.759673
\n– SV = 8562
\n– BSV = 8519
\n– Threshold b = 1.0672944<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 250
\n\tn: 82
\n\tC: 100.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 282
\n– Total CPU time: 1395.320000
\n– Total kernel evaluations: 4865895
\n– Total inner solver iterations: 21797479
\n– Total projector iterations: 108665145
\n– Total preparation time: 0.740000
\n– Total inner solver time: 1390.360000
\n– Total gradient updating time: 1.730000
\n– Objective function value: -8538768.868464
\n– SV = 8558
\n– BSV = 8520
\n– Threshold b = 1.0672322<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 250
\n\tn: 82
\n\tC: 1000.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 85
\n– Total CPU time: 101.460000
\n– Total kernel evaluations: 591626401
\n– Total inner solver iterations: 7145
\n– Total projector iterations: 58438
\n– Total preparation time: 0.980000
\n– Total inner solver time: 1.250000
\n– Total gradient updating time: 98.470000
\n– Objective function value: -8148.187334
\n– SV = 8981
\n– BSV = 8920
\n– Threshold b = 1.6513286<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.045454545
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 87
\n– Total CPU time: 97.030000
\n– Total kernel evaluations: 544768874
\n– Total inner solver iterations: 28907
\n– Total projector iterations: 211052
\n– Total preparation time: 0.970000
\n– Total inner solver time: 4.620000
\n– Total gradient updating time: 90.710000
\n– Objective function value: -61036.540860
\n– SV = 7084
\n– BSV = 7004
\n– Threshold b = 3.8870853<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.045454545
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 80
\n– Total CPU time: 97.800000
\n– Total kernel evaluations: 421549004
\n– Total inner solver iterations: 145499
\n– Total projector iterations: 994646
\n– Total preparation time: 0.910000
\n– Total inner solver time: 25.660000
\n– Total gradient updating time: 70.500000
\n– Objective function value: -418362.839758
\n– SV = 4937
\n– BSV = 4796
\n– Threshold b = 14.312438<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.045454545
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 65
\n– Total CPU time: 232.080000
\n– Total kernel evaluations: 380291875
\n– Total inner solver iterations: 716265
\n– Total projector iterations: 4275642
\n– Total preparation time: 0.740000
\n– Total inner solver time: 166.440000
\n– Total gradient updating time: 64.340000
\n– Objective function value: -2971165.282858
\n– SV = 3480
\n– BSV = 3245
\n– Threshold b = 21.069942<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.045454545
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 88
\n– Total CPU time: 104.290000
\n– Total kernel evaluations: 735966829
\n– Total inner solver iterations: 1469
\n– Total projector iterations: 17525
\n– Total preparation time: 0.720000
\n– Total inner solver time: 0.330000
\n– Total gradient updating time: 102.520000
\n– Objective function value: -9693.422795
\n– SV = 9795
\n– BSV = 9652
\n– Threshold b = 1.0002741<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.045454545
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 102
\n– Total CPU time: 116.410000
\n– Total kernel evaluations: 819274141
\n– Total inner solver iterations: 3175
\n– Total projector iterations: 28730
\n– Total preparation time: 0.850000
\n– Total inner solver time: 0.760000
\n– Total gradient updating time: 113.920000
\n– Objective function value: -95821.714612
\n– SV = 9924
\n– BSV = 9545
\n– Threshold b = 1.0022653<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.045454545
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 96
\n– Total CPU time: 103.320000
\n– Total kernel evaluations: 726489119
\n– Total inner solver iterations: 5481
\n– Total projector iterations: 33279
\n– Total preparation time: 0.760000
\n– Total inner solver time: 0.980000
\n– Total gradient updating time: 100.740000
\n– Objective function value: -854438.151385
\n– SV = 9582
\n– BSV = 9388
\n– Threshold b = 1.0207068<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.045454545
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 90
\n– Total CPU time: 94.240000
\n– Total kernel evaluations: 633955717
\n– Total inner solver iterations: 21137
\n– Total projector iterations: 100497
\n– Total preparation time: 0.770000
\n– Total inner solver time: 3.890000
\n– Total gradient updating time: 88.860000
\n– Objective function value: -6077587.618220
\n– SV = 7319
\n– BSV = 7050
\n– Threshold b = 1.0391432<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/ijcnn1
\n\tNumber of training documents: 49990
\n\tModel file: datasets\/ijcnn1.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.045454545
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 67
\n– Total CPU time: 3.500000
\n– Total kernel evaluations: 1059321
\n– Total inner solver iterations: 23068
\n– Total projector iterations: 100645
\n– Total preparation time: 0.090000
\n– Total inner solver time: 2.860000
\n– Total gradient updating time: 0.260000
\n– Objective function value: -765.410284
\n– SV = 1030
\n– BSV = 686
\n– Threshold b = 1.0288505<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 210
\n– Total CPU time: 29.560000
\n– Total kernel evaluations: 3219410
\n– Total inner solver iterations: 212952
\n– Total projector iterations: 754805
\n– Total preparation time: 0.340000
\n– Total inner solver time: 27.720000
\n– Total gradient updating time: 0.790000
\n– Objective function value: -7008.300359
\n– SV = 964
\n– BSV = 591
\n– Threshold b = 1.0308125<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 250
\n\tn: 82
\n\tC: 10.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 1062
\n– Total CPU time: 412.510000
\n– Total kernel evaluations: 15738116
\n– Total inner solver iterations: 3083160
\n– Total projector iterations: 9942641
\n– Total preparation time: 2.050000
\n– Total inner solver time: 403.000000
\n– Total gradient updating time: 3.350000
\n– Objective function value: -68985.659321
\n– SV = 964
\n– BSV = 573
\n– Threshold b = 1.0232359<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 250
\n\tn: 82
\n\tC: 100.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 4997
\n– Total CPU time: 5524.730000
\n– Total kernel evaluations: 64585733
\n– Total inner solver iterations: 42924001
\n– Total projector iterations: 118559940
\n– Total preparation time: 8.920000
\n– Total inner solver time: 5477.760000
\n– Total gradient updating time: 18.710000
\n– Objective function value: -688535.715865
\n– SV = 969
\n– BSV = 564
\n– Threshold b = 1.0271917<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1000.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 20
\n– Total CPU time: 12.540000
\n– Total kernel evaluations: 61128257
\n– Total inner solver iterations: 1414
\n– Total projector iterations: 11276
\n– Total preparation time: 0.180000
\n– Total inner solver time: 0.380000
\n– Total gradient updating time: 11.910000
\n– Objective function value: -1372.011038
\n– SV = 1626
\n– BSV = 1379
\n– Threshold b = -1.852077<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0033333333
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 25
\n– Total CPU time: 15.460000
\n– Total kernel evaluations: 60896498
\n– Total inner solver iterations: 8819
\n– Total projector iterations: 67381
\n– Total preparation time: 0.210000
\n– Total inner solver time: 2.940000
\n– Total gradient updating time: 12.190000
\n– Objective function value: -10422.687861
\n– SV = 1470
\n– BSV = 1068
\n– Threshold b = -7.9937594<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0033333333
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 40
\n– Total CPU time: 26.510000
\n– Total kernel evaluations: 85629123
\n– Total inner solver iterations: 20171
\n– Total projector iterations: 120366
\n– Total preparation time: 0.380000
\n– Total inner solver time: 8.330000
\n– Total gradient updating time: 17.680000
\n– Objective function value: -72136.035804
\n– SV = 1292
\n– BSV = 636
\n– Threshold b = -12.796448<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0033333333
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance temporary changed to: 1.000000e-04
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 89
\n– Total CPU time: 110.450000
\n– Total kernel evaluations: 273026393
\n– Total inner solver iterations: 118568
\n– Total projector iterations: 578024
\n– Total preparation time: 0.780000
\n– Total inner solver time: 54.620000
\n– Total gradient updating time: 54.680000
\n– Objective function value: -491864.846133
\n– SV = 1419
\n– BSV = 361
\n– Threshold b = -12.330358<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0033333333
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 12
\n– Total CPU time: 7.520000
\n– Total kernel evaluations: 45450555
\n– Total inner solver iterations: 121
\n– Total projector iterations: 1292
\n– Total preparation time: 0.070000
\n– Total inner solver time: 0.060000
\n– Total gradient updating time: 7.320000
\n– Objective function value: -1479.809634
\n– SV = 1681
\n– BSV = 1351
\n– Threshold b = 0.99982015<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0033333333
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 13
\n– Total CPU time: 8.400000
\n– Total kernel evaluations: 50592021
\n– Total inner solver iterations: 313
\n– Total projector iterations: 2839
\n– Total preparation time: 0.120000
\n– Total inner solver time: 0.070000
\n– Total gradient updating time: 8.190000
\n– Objective function value: -14781.925814
\n– SV = 1770
\n– BSV = 1339
\n– Threshold b = 0.99955361<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0033333333
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance changed to: 0.000500
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 36
\n– Total CPU time: 16.080000
\n– Total kernel evaluations: 85475955
\n– Total inner solver iterations: 2729
\n– Total projector iterations: 20399
\n– Total preparation time: 0.240000
\n– Total inner solver time: 1.130000
\n– Total gradient updating time: 14.590000
\n– Objective function value: -146248.004254
\n– SV = 2072
\n– BSV = 1284
\n– Threshold b = 0.99988817<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0033333333
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 73
\n– Total CPU time: 34.580000
\n– Total kernel evaluations: 150267557
\n– Total inner solver iterations: 16438
\n– Total projector iterations: 94072
\n– Total preparation time: 0.460000
\n– Total inner solver time: 7.770000
\n– Total gradient updating time: 25.990000
\n– Objective function value: -1344717.883913
\n– SV = 2462
\n– BSV = 1111
\n– Threshold b = 1.0000202<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/w7a
\n\tNumber of training documents: 24692
\n\tModel file: datasets\/w7a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0033333333
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000<\/p>\n\n\n\n\n\n

——+———–+———–+————-+———–+————–
\nInner tolerance changed to: 0.000250
\nInner tolerance changed to: 0.000125
\nInner tolerance changed to: 0.000063
\nInner tolerance changed to: 0.000050
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 584
\n– Total CPU time: 31.290000
\n– Total kernel evaluations: 10144676
\n– Total inner solver iterations: 17647
\n– Total projector iterations: 73673
\n– Total preparation time: 2.620000
\n– Total inner solver time: 2.230000
\n– Total gradient updating time: 18.480000
\n– Objective function value: -5345.120708
\n– SV = 10866
\n– BSV = 5383
\n– Threshold b = 0.28860555<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 250
\n\tn: 82
\n\tC: 1.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance changed to: 0.000250
\nInner tolerance changed to: 0.000125
\nInner tolerance changed to: 0.000063
\nInner tolerance changed to: 0.000050
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 1441
\n– Total CPU time: 78.310000
\n– Total kernel evaluations: 25011055
\n– Total inner solver iterations: 45699
\n– Total projector iterations: 153447
\n– Total preparation time: 6.320000
\n– Total inner solver time: 7.430000
\n– Total gradient updating time: 45.490000
\n– Objective function value: -15202.782306
\n– SV = 7940
\n– BSV = 734
\n– Threshold b = 0.56187685<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 250
\n\tn: 82
\n\tC: 10.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance changed to: 0.000250
\nInner tolerance changed to: 0.000125
\nInner tolerance changed to: 0.000063
\nInner tolerance changed to: 0.000050
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 1851
\n– Total CPU time: 109.020000
\n– Total kernel evaluations: 32123325
\n– Total inner solver iterations: 110236
\n– Total projector iterations: 345706
\n– Total preparation time: 8.390000
\n– Total inner solver time: 17.530000
\n– Total gradient updating time: 58.450000
\n– Objective function value: -47124.509207
\n– SV = 7187
\n– BSV = 254
\n– Threshold b = 0.99929533<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 250
\n\tn: 82
\n\tC: 100.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance changed to: 0.000250
\nInner tolerance changed to: 0.000125
\nInner tolerance changed to: 0.000063
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 1875
\n– Total CPU time: 127.050000
\n– Total kernel evaluations: 32539653
\n– Total inner solver iterations: 220083
\n– Total projector iterations: 690150
\n– Total preparation time: 8.110000
\n– Total inner solver time: 34.790000
\n– Total gradient updating time: 59.100000
\n– Objective function value: -297003.979512
\n– SV = 6630
\n– BSV = 202
\n– Threshold b = 0.99924725<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 250
\n\tn: 82
\n\tC: 1000.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 302
\n– Total CPU time: 2069.650000
\n– Total kernel evaluations: 4367576358
\n– Total inner solver iterations: 2498
\n– Total projector iterations: 39055
\n– Total preparation time: 6.330000
\n– Total inner solver time: 0.590000
\n– Total gradient updating time: 2058.990000
\n– Objective function value: -44319.154350
\n– SV = 44520
\n– BSV = 44387
\n– Threshold b = 0.99298363<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 4.7714477e-05
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 300
\n– Total CPU time: 3312.370000
\n– Total kernel evaluations: 5288969003
\n– Total inner solver iterations: 2973
\n– Total projector iterations: 34310
\n– Total preparation time: 6.910000
\n– Total inner solver time: 0.940000
\n– Total gradient updating time: 3300.410000
\n– Objective function value: -429079.222957
\n– SV = 44606
\n– BSV = 44327
\n– Threshold b = 0.92962324<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 4.7714477e-05
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 271
\n– Total CPU time: 3204.800000
\n– Total kernel evaluations: 4752992928
\n– Total inner solver iterations: 3749
\n– Total projector iterations: 31864
\n– Total preparation time: 6.030000
\n– Total inner solver time: 1.020000
\n– Total gradient updating time: 3193.830000
\n– Objective function value: -3138083.940593
\n– SV = 40017
\n– BSV = 39443
\n– Threshold b = 0.38985816<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 4.7714477e-05
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 172
\n– Total CPU time: 1876.410000
\n– Total kernel evaluations: 2757952705
\n– Total inner solver iterations: 4327
\n– Total projector iterations: 26856
\n– Total preparation time: 3.830000
\n– Total inner solver time: 1.000000
\n– Total gradient updating time: 1868.990000
\n– Objective function value: -14389647.447924
\n– SV = 21001
\n– BSV = 18849
\n– Threshold b = -2.4101211<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 4.7714477e-05
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 997
\n– Total CPU time: 2191.910000
\n– Total kernel evaluations: 3444561505
\n– Total inner solver iterations: 2849
\n– Total projector iterations: 61973
\n– Total preparation time: 10.580000
\n– Total inner solver time: 1.250000
\n– Total gradient updating time: 2168.590000
\n– Objective function value: -44475.999767
\n– SV = 44580
\n– BSV = 44120
\n– Threshold b = 1<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 4.7714477e-05
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 1040
\n– Total CPU time: 11431.020000
\n– Total kernel evaluations: 20395582400
\n– Total inner solver iterations: 3131
\n– Total projector iterations: 66539
\n– Total preparation time: 10.030000
\n– Total inner solver time: 2.320000
\n– Total gradient updating time: 11405.470000
\n– Objective function value: -444760.005597
\n– SV = 45153
\n– BSV = 37833
\n– Threshold b = 1<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 4.7714477e-05
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 999
\n– Total CPU time: 5153.400000
\n– Total kernel evaluations: 9578341327
\n– Total inner solver iterations: 3077
\n– Total projector iterations: 72333
\n– Total preparation time: 9.610000
\n– Total inner solver time: 1.750000
\n– Total gradient updating time: 5129.430000
\n– Objective function value: -4447600.000266
\n– SV = 44601
\n– BSV = 42818
\n– Threshold b = 1<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 4.7714477e-05
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 1025
\n– Total CPU time: 7627.560000
\n– Total kernel evaluations: 12316006268
\n– Total inner solver iterations: 3075
\n– Total projector iterations: 68368
\n– Total preparation time: 10.790000
\n– Total inner solver time: 1.950000
\n– Total gradient updating time: 7600.670000
\n– Objective function value: -44475999.992612
\n– SV = 44994
\n– BSV = 37925
\n– Threshold b = 1<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/real-sim
\n\tNumber of training documents: 72309
\n\tModel file: datasets\/real-sim.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 4.7714477e-05
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 54
\n– Total CPU time: 2.750000
\n– Total kernel evaluations: 849735
\n– Total inner solver iterations: 18883
\n– Total projector iterations: 84324
\n– Total preparation time: 0.100000
\n– Total inner solver time: 2.340000
\n– Total gradient updating time: 0.160000
\n– Objective function value: -536.967720
\n– SV = 793
\n– BSV = 475
\n– Threshold b = 1.0270783<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 127
\n– Total CPU time: 16.410000
\n– Total kernel evaluations: 1882418
\n– Total inner solver iterations: 119410
\n– Total projector iterations: 428403
\n– Total preparation time: 0.180000
\n– Total inner solver time: 15.540000
\n– Total gradient updating time: 0.320000
\n– Objective function value: -4757.225072
\n– SV = 693
\n– BSV = 383
\n– Threshold b = 1.0510835<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 250
\n\tn: 82
\n\tC: 10.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 527
\n– Total CPU time: 221.750000
\n– Total kernel evaluations: 7455115
\n– Total inner solver iterations: 1652649
\n– Total projector iterations: 5487240
\n– Total preparation time: 0.890000
\n– Total inner solver time: 218.280000
\n– Total gradient updating time: 1.180000
\n– Objective function value: -46181.507828
\n– SV = 701
\n– BSV = 357
\n– Threshold b = 1.0290578<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 250
\n\tn: 82
\n\tC: 100.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 1692
\n– Total CPU time: 3689.320000
\n– Total kernel evaluations: 24669211
\n– Total inner solver iterations: 28860152
\n– Total projector iterations: 80059003
\n– Total preparation time: 2.790000
\n– Total inner solver time: 3677.290000
\n– Total gradient updating time: 4.810000
\n– Objective function value: -460005.491576
\n– SV = 702
\n– BSV = 362
\n– Threshold b = 1.0214426<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 250
\n\tn: 82
\n\tC: 1000.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 14
\n– Total CPU time: 6.340000
\n– Total kernel evaluations: 30013562
\n– Total inner solver iterations: 1145
\n– Total projector iterations: 8991
\n– Total preparation time: 0.150000
\n– Total inner solver time: 0.260000
\n– Total gradient updating time: 5.900000
\n– Objective function value: -994.832759
\n– SV = 1157
\n– BSV = 975
\n– Threshold b = -1.0753524<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0033333333
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 19
\n– Total CPU time: 8.030000
\n– Total kernel evaluations: 30092787
\n– Total inner solver iterations: 5170
\n– Total projector iterations: 39156
\n– Total preparation time: 0.190000
\n– Total inner solver time: 1.720000
\n– Total gradient updating time: 6.090000
\n– Objective function value: -7616.446071
\n– SV = 1083
\n– BSV = 752
\n– Threshold b = -6.8529281<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0033333333
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 33
\n– Total CPU time: 13.610000
\n– Total kernel evaluations: 28948953
\n– Total inner solver iterations: 16131
\n– Total projector iterations: 97311
\n– Total preparation time: 0.240000
\n– Total inner solver time: 6.850000
\n– Total gradient updating time: 6.440000
\n– Objective function value: -51682.466431
\n– SV = 1007
\n– BSV = 454
\n– Threshold b = -11.909778<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0033333333
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 62
\n– Total CPU time: 47.130000
\n– Total kernel evaluations: 34841092
\n– Total inner solver iterations: 88132
\n– Total projector iterations: 393440
\n– Total preparation time: 0.390000
\n– Total inner solver time: 38.120000
\n– Total gradient updating time: 8.410000
\n– Objective function value: -341445.797873
\n– SV = 941
\n– BSV = 264
\n– Threshold b = -12.011937<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0033333333
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 10
\n– Total CPU time: 4.110000
\n– Total kernel evaluations: 24215792
\n– Total inner solver iterations: 75
\n– Total projector iterations: 911
\n– Total preparation time: 0.070000
\n– Total inner solver time: 0.010000
\n– Total gradient updating time: 3.990000
\n– Objective function value: -1049.893563
\n– SV = 1298
\n– BSV = 1000
\n– Threshold b = 0.99969557<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0033333333
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 10
\n– Total CPU time: 4.410000
\n– Total kernel evaluations: 25689503
\n– Total inner solver iterations: 233
\n– Total projector iterations: 2080
\n– Total preparation time: 0.070000
\n– Total inner solver time: 0.080000
\n– Total gradient updating time: 4.240000
\n– Objective function value: -10490.123533
\n– SV = 1334
\n– BSV = 933
\n– Threshold b = 0.99957658<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0033333333
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 27
\n– Total CPU time: 7.430000
\n– Total kernel evaluations: 36073091
\n– Total inner solver iterations: 1966
\n– Total projector iterations: 14734
\n– Total preparation time: 0.210000
\n– Total inner solver time: 0.820000
\n– Total gradient updating time: 6.350000
\n– Objective function value: -104053.955914
\n– SV = 1600
\n– BSV = 863
\n– Threshold b = 0.9993543<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0033333333
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 50
\n– Total CPU time: 15.690000
\n– Total kernel evaluations: 55726483
\n– Total inner solver iterations: 11403
\n– Total projector iterations: 66076
\n– Total preparation time: 0.340000
\n– Total inner solver time: 5.080000
\n– Total gradient updating time: 10.140000
\n– Objective function value: -967295.228894
\n– SV = 1870
\n– BSV = 774
\n– Threshold b = 1.0000532<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/web6a
\n\tNumber of training documents: 17188
\n\tModel file: datasets\/web6a.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0033333333
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance changed to: 0.000250
\nInner tolerance changed to: 0.000125
\nInner tolerance changed to: 0.000063
\nInner tolerance changed to: 0.000050
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 1472
\n– Total CPU time: 186.250000
\n– Total kernel evaluations: 25022943
\n– Total inner solver iterations: 412971
\n– Total projector iterations: 1704512
\n– Total preparation time: 14.620000
\n– Total inner solver time: 57.820000
\n– Total gradient updating time: 96.500000
\n– Objective function value: -5966.194721
\n– SV = 6262
\n– BSV = 5754
\n– Threshold b = 3.9693857<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 250
\n\tn: 82
\n\tC: 1.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance changed to: 0.000250
\nInner tolerance changed to: 0.000125
\nInner tolerance changed to: 0.000063
\nInner tolerance changed to: 0.000050
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 14015
\n– Total CPU time: 1933.300000
\n– Total kernel evaluations: 243132233
\n– Total inner solver iterations: 4831504
\n– Total projector iterations: 15117521
\n– Total preparation time: 141.870000
\n– Total inner solver time: 713.420000
\n– Total gradient updating time: 912.870000
\n– Objective function value: -59185.482034
\n– SV = 6231
\n– BSV = 5673
\n– Threshold b = 3.9980961<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 250
\n\tn: 82
\n\tC: 10.000000
\n\tkernel type: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000<\/p>\n\n\n\n\n\n

——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 23045
\n– Total CPU time: 18804.830000
\n– Total kernel evaluations: 752832515
\n– Total inner solver iterations: 49724952
\n– Total projector iterations: 153525280
\n– Total preparation time: 448.540000
\n– Total inner solver time: 16503.300000
\n– Total gradient updating time: 1575.860000
\n– Objective function value: -589894.763230
\n– SV = 6202
\n– BSV = 5627
\n– Threshold b = 4.034682<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n Training file: datasets\/mnist
\n Number of training documents: 60000
\n Model file: datasets\/mnist.out
\n q: 400
\n n: 132
\n C: 100.000000
\n kernel type: 0
\n cache size: 40Mb
\n Stopping tolerance: 0.001000<\/p>\n\n\n\n\n\n

——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 67
\n– Total CPU time: 764.540000
\n– Total kernel evaluations: 657131086
\n– Total inner solver iterations: 3073
\n– Total projector iterations: 26363
\n– Total preparation time: 2.420000
\n– Total inner solver time: 0.610000
\n– Total gradient updating time: 760.740000
\n– Objective function value: -5983.342854
\n– SV = 7202
\n– BSV = 7001
\n– Threshold b = 12.332663<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0012820513
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 59
\n– Total CPU time: 952.300000
\n– Total kernel evaluations: 810123860
\n– Total inner solver iterations: 8724
\n– Total projector iterations: 68829
\n– Total preparation time: 2.080000
\n– Total inner solver time: 2.690000
\n– Total gradient updating time: 946.830000
\n– Objective function value: -33125.151425
\n– SV = 4731
\n– BSV = 4095
\n– Threshold b = 44.368969<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0012820513
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\nInner tolerance changed to: 0.000500
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 154
\n– Total CPU time: 3392.800000
\n– Total kernel evaluations: 2848477937
\n– Total inner solver iterations: 29830
\n– Total projector iterations: 184900
\n– Total preparation time: 4.620000
\n– Total inner solver time: 12.900000
\n– Total gradient updating time: 3373.470000
\n– Objective function value: -127481.747198
\n– SV = 2863
\n– BSV = 1247
\n– Threshold b = 90.512381<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0012820513
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 248
\n– Total CPU time: 5684.250000
\n– Total kernel evaluations: 4879700511
\n– Total inner solver iterations: 69872
\n– Total projector iterations: 345422
\n– Total preparation time: 8.730000
\n– Total inner solver time: 34.260000
\n– Total gradient updating time: 5638.310000
\n– Objective function value: -239311.183886
\n– SV = 2476
\n– BSV = 26
\n– Threshold b = 109.3299<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 2
\n\tkernel parameter -g: 0.0012820513
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 106
\n– Total CPU time: 1313.940000
\n– Total kernel evaluations: 960547578
\n– Total inner solver iterations: 1371
\n– Total projector iterations: 13543
\n– Total preparation time: 3.550000
\n– Total inner solver time: 0.240000
\n– Total gradient updating time: 1308.840000
\n– Objective function value: -10756.740226
\n– SV = 11759
\n– BSV = 11646
\n– Threshold b = 1.0711884<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 450
\n\tn: 150
\n\tC: 1.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0012820513
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 73
\n– Total CPU time: 1082.470000
\n– Total kernel evaluations: 756270880
\n– Total inner solver iterations: 2032
\n– Total projector iterations: 13826
\n– Total preparation time: 2.780000
\n– Total inner solver time: 0.380000
\n– Total gradient updating time: 1078.450000
\n– Objective function value: -73151.130673
\n– SV = 9103
\n– BSV = 8848
\n– Threshold b = 1.0840146<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 450
\n\tn: 150
\n\tC: 10.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0012820513
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 60
\n– Total CPU time: 1202.840000
\n– Total kernel evaluations: 762058823
\n– Total inner solver iterations: 6849
\n– Total projector iterations: 32440
\n– Total preparation time: 2.210000
\n– Total inner solver time: 2.310000
\n– Total gradient updating time: 1197.500000
\n– Objective function value: -389311.149164
\n– SV = 5527
\n– BSV = 4795
\n– Threshold b = 0.98938308<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 450
\n\tn: 150
\n\tC: 100.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0012820513
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000
\n——+———–+———–+————-+———–+————–
\n——+———–+———–+————-+———–+————–<\/p>\n\n\n\n\n\n

– TOTAL ITERATIONS: 74
\n– Total CPU time: 2349.890000
\n– Total kernel evaluations: 1432669791
\n– Total inner solver iterations: 20124
\n– Total projector iterations: 71051
\n– Total preparation time: 2.660000
\n– Total inner solver time: 9.980000
\n– Total gradient updating time: 2336.220000
\n– Objective function value: -1547134.718773
\n– SV = 3482
\n– BSV = 1604
\n– Threshold b = 0.9350593<\/p>\n\n\n\n\n\n

TRAINING PARAMETERS:
\n\tTraining file: datasets\/mnist
\n\tNumber of training documents: 60000
\n\tModel file: datasets\/mnist.out
\n\tq: 450
\n\tn: 150
\n\tC: 1000.000000
\n\tkernel type: 1
\n\tkernel parameter -d: 3
\n\tkernel parameter -s: 0.0012820513
\n\tkernel parameter -r: 0
\n\tcache size: 40Mb
\n\tStopping tolerance: 0.001000<\/p>\n\n\n\r\n\t\t\t<\/div>\r\n\t\t<\/div>\r\n\t<\/div>\r\n<\/section>\r\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1075,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"featured_post":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-528","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/people.clas.ufl.edu\/hager\/wp-json\/wp\/v2\/pages\/528","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/people.clas.ufl.edu\/hager\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/people.clas.ufl.edu\/hager\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/people.clas.ufl.edu\/hager\/wp-json\/wp\/v2\/users\/1075"}],"replies":[{"embeddable":true,"href":"https:\/\/people.clas.ufl.edu\/hager\/wp-json\/wp\/v2\/comments?post=528"}],"version-history":[{"count":2,"href":"https:\/\/people.clas.ufl.edu\/hager\/wp-json\/wp\/v2\/pages\/528\/revisions"}],"predecessor-version":[{"id":773,"href":"https:\/\/people.clas.ufl.edu\/hager\/wp-json\/wp\/v2\/pages\/528\/revisions\/773"}],"wp:attachment":[{"href":"https:\/\/people.clas.ufl.edu\/hager\/wp-json\/wp\/v2\/media?parent=528"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}