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lambda_exploration_kemp.txt
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Loaded voltage protocol for model fitting.
Loaded voltage protocol for validation.
Inner optimisation is split into 27 segments based on protocol steps.
Number of B-spline coeffs per segment: 32.
Produced synthetic data for the Kemp model based on the pre-loaded voltage protocol.
===========================================================================================================
Starting optimisation for lambda: 1.00E+08.
Iteration: 0
Best parameters: [ -8.29556556 -2.45229623 -10.30956958 -2.81412391 -2.59744711
-4.67750616 -5.32992694 -3.48565224 -1.68745235]
Best objective: 4872.8428226873775
Mean objective: 6516.080353327307
Inner objective at best sample: 124353.4301884482
Gradient objective at best sample: 0.0011948058736576082
Time elapsed: 159.41637873649597
Iteration: 1
Best parameters: [ -8.22000132 -2.74406572 -10.21052268 -2.76278914 -2.57985295
-4.73141699 -4.92472225 -3.46171207 -1.77009098]
Best objective: 3705.797714168531
Mean objective: 6018.826616352393
Inner objective at best sample: 307949.38153771684
Gradient objective at best sample: 0.0030424358382354828
Time elapsed: 159.1194188594818
Iteration: 2
Best parameters: [ -8.07067479 -2.45989434 -10.10524647 -2.75102279 -2.79379146
-4.74114562 -5.12954454 -3.63037136 -1.52198005]
Best objective: 2809.138737979198
Mean objective: 4720.843538537866
Inner objective at best sample: 81859.81793036676
Gradient objective at best sample: 0.0007905067919238755
Time elapsed: 163.57054543495178
Iteration: 3
Best parameters: [ -7.58578778 -2.981057 -10.29743682 -2.63380927 -2.5719872
-4.51846336 -5.0347814 -3.56168713 -1.34428147]
Best objective: 2236.0788866525663
Mean objective: 5668.839297366385
Inner objective at best sample: 195750.27431263632
Gradient objective at best sample: 0.0019351419542598374
Time elapsed: 172.91871762275696
Iteration: 4
Best parameters: [-7.76559617 -2.64756935 -9.88250139 -2.7235858 -2.88209686 -5.12953418
-5.16804583 -3.41635366 -1.56986767]
Best objective: 2512.3629282801717
Mean objective: 5241.9832937379115
Inner objective at best sample: 269026.35669294005
Gradient objective at best sample: 0.0026651399376465983
Time elapsed: 152.8265347480774
Iteration: 5
Best parameters: [ -7.32479161 -2.69259484 -10.44961639 -2.65583991 -2.57866166
-5.24207674 -5.08736561 -3.72913641 -1.62851244]
Best objective: 2630.797864069276
Mean objective: 4920.71869610224
Inner objective at best sample: 79265.4368087093
Gradient objective at best sample: 0.0007663463894464003
Time elapsed: 160.28438591957092
Iteration: 6
Best parameters: [ -6.59036525 -2.98751924 -10.37094281 -2.46754177 -2.69888783
-4.64101249 -4.73206527 -3.72040231 -1.92506773]
Best objective: 1389.924965804287
Mean objective: 7609.1351177616325
Inner objective at best sample: 2898451.45067023
Gradient objective at best sample: 0.028970615257044256
Time elapsed: 163.30910181999207
Iteration: 7
Best parameters: [ -7.2490687 -3.01043697 -10.45781064 -2.42266975 -2.67701614
-4.94492818 -4.54951921 -3.4592765 -1.7471342 ]
Best objective: 1880.0104545830775
Mean objective: 7621.949011377681
Inner objective at best sample: 10687132.154786086
Gradient objective at best sample: 0.10685252144331502
Time elapsed: 156.05667352676392
Iteration: 8
Best parameters: [ -6.07920279 -3.86250041 -10.03373312 -2.37794556 -2.90674218
-5.21994775 -4.16658592 -3.19382694 -2.35163702]
Best objective: 776.0256447030544
Mean objective: 6514.795389103059
Inner objective at best sample: 39516496.84626595
Gradient objective at best sample: 0.3951572082062125
Time elapsed: 169.7341730594635
Iteration: 9
Best parameters: [-6.51062488 -3.95236259 -9.35560284 -2.84381545 -3.07597275 -4.4565941
-4.3058108 -3.4846254 -2.43095612]
Best objective: 509.3441404122666
Mean objective: 5985.231435991672
Inner objective at best sample: 905148.9115375851
Gradient objective at best sample: 0.009046395673971728
Time elapsed: 170.81410789489746
Iteration: 10
Best parameters: [-6.69909275 -3.83793708 -9.74332848 -2.89745991 -2.66331255 -4.4669269
-4.46814996 -3.60188955 -2.14654119]
Best objective: 873.716285317705
Mean objective: 6856.89968014746
Inner objective at best sample: 281146.2100657498
Gradient objective at best sample: 0.002802724937804321
Time elapsed: 177.697509765625
Iteration: 11
Best parameters: [ -5.29853403 -4.35803372 -10.22983534 -2.61661738 -2.66758832
-5.15770343 -4.30611534 -3.62978374 -2.31010804]
Best objective: 1262.8845445982115
Mean objective: 5450.459203929377
Inner objective at best sample: 415964.3892834196
Gradient objective at best sample: 0.004147015047388214
Time elapsed: 173.12450551986694
Iteration: 12
Best parameters: [-6.05742503 -3.70683446 -9.71198887 -2.53974751 -2.92418308 -5.64013348
-4.72385266 -3.44412507 -2.01726033]
Best objective: 555.4578089035898
Mean objective: 4630.791541859566
Inner objective at best sample: 2949646.895228707
Gradient objective at best sample: 0.029490914374198037
Time elapsed: 189.00711512565613
Iteration: 13
Best parameters: [-6.36333502 -3.36867029 -9.02152948 -2.91315158 -2.65311006 -5.04043405
-4.71504845 -3.69827472 -1.67928258]
Best objective: 543.3219416159795
Mean objective: 2934.929281031947
Inner objective at best sample: 104295.67538141196
Gradient objective at best sample: 0.0010375235343979597
Time elapsed: 167.22156381607056
Iteration: 14
Best parameters: [-6.42128328 -3.06311386 -9.54382343 -2.84494223 -2.92220181 -4.83161905
-4.39624075 -3.42002385 -2.25624341]
Best objective: 534.5816292312317
Mean objective: 1690.778136424893
Inner objective at best sample: 1358525.6457254633
Gradient objective at best sample: 0.013579910640962319
Time elapsed: 136.2145392894745
Iteration: 15
Best parameters: [-6.48356915 -3.94411636 -9.97634564 -2.80250889 -2.58891145 -4.93995888
-3.75214617 -3.5087673 -2.53366419]
Best objective: 437.71561087988573
Mean objective: 1532.0701914662047
Inner objective at best sample: 2929110.4139274987
Gradient objective at best sample: 0.029286726983166186
Time elapsed: 152.27326560020447
Iteration: 16
Best parameters: [ -6.19752226 -3.5738899 -10.42441305 -2.77761802 -2.79741073
-5.05211956 -4.13998133 -3.57422013 -2.42126309]
Best objective: 436.4766141946882
Mean objective: 1292.0242570080386
Inner objective at best sample: 636957.7427618745
Gradient objective at best sample: 0.006365212661476798
Time elapsed: 156.9685297012329
Iteration: 17
Best parameters: [-6.14013321 -3.43288242 -9.95660929 -2.7394515 -2.95827583 -4.69707255
-4.02939485 -3.53521425 -2.54779972]
Best objective: 333.00539377236095
Mean objective: 943.6494222319666
Inner objective at best sample: 1127264.3991536119
Gradient objective at best sample: 0.011269313937598394
Time elapsed: 183.2053472995758
Iteration: 18
Best parameters: [-6.16873321 -3.64039976 -9.93983258 -2.74037898 -2.76253745 -5.126658
-3.74897554 -3.52857041 -2.59496323]
Best objective: 414.8714808785387
Mean objective: 776.4388648728444
Inner objective at best sample: 2374998.615828788
Gradient objective at best sample: 0.023745837443479096
Time elapsed: 167.95881390571594
Iteration: 19
Best parameters: [-5.79890731 -3.50822643 -9.58107135 -2.74716025 -2.72896988 -4.77717358
-3.85163576 -3.58098754 -2.52225446]
Best objective: 387.1324162257722
Mean objective: 658.1432722253599
Inner objective at best sample: 1238484.7219662378
Gradient objective at best sample: 0.012380975895500121
Time elapsed: 198.43993186950684
Iteration: 20
Best parameters: [ -6.05867997 -3.45626037 -10.26103399 -2.67436092 -2.89343712
-5.0725749 -4.02666978 -3.44150946 -2.61352104]
Best objective: 388.42246306577056
Mean objective: 696.653010657006
Inner objective at best sample: 2722037.1037466424
Gradient objective at best sample: 0.027216486812835766
Time elapsed: 174.64168739318848
Iteration: 21
Best parameters: [-6.32517142 -3.36229026 -9.72473057 -2.8361976 -2.54377174 -5.0231332
-3.86204435 -3.45989965 -2.37557644]
Best objective: 335.55399324237294
Mean objective: 680.3177670448368
Inner objective at best sample: 3731379.52186822
Gradient objective at best sample: 0.03731043967874978
Time elapsed: 189.8058602809906
Iteration: 22
Best parameters: [ -6.07775605 -3.3439873 -10.15198552 -2.71070445 -2.57278324
-4.7191593 -3.27858308 -3.445864 -2.83955472]
Best objective: 334.6602784751524
Mean objective: 574.1514552770175
Inner objective at best sample: 16570710.374858482
Gradient objective at best sample: 0.16570375714580007
Time elapsed: 192.79033637046814
Iteration: 23
Best parameters: [ -5.82039666 -3.19608479 -10.32532287 -2.73381958 -2.39025459
-4.51501245 -3.1028024 -3.4273829 -2.84936931]
Best objective: 250.75731765196156
Mean objective: 507.553212667994
Inner objective at best sample: 19369888.586658694
Gradient objective at best sample: 0.19369637829341044
Time elapsed: 202.27858638763428
Iteration: 24
Best parameters: [-5.88430359 -3.08741464 -9.85963896 -2.86813125 -2.52198319 -4.46719455
-3.43174585 -3.43352091 -2.65211286]
Best objective: 257.86688688833186
Mean objective: 494.4329683765902
Inner objective at best sample: 15497639.567507016
Gradient objective at best sample: 0.15497381700620128
Time elapsed: 198.47137236595154
Iteration: 25
Best parameters: [ -5.84741543 -3.10810757 -10.41211872 -2.73984 -2.74175503
-4.55553781 -3.79256007 -3.56177065 -2.63064926]
Best objective: 257.10510438953463
Mean objective: 540.2229174149757
Inner objective at best sample: 1660321.6617404066
Gradient objective at best sample: 0.01660064556636017
Time elapsed: 176.1215422153473
Iteration: 26
Best parameters: [-5.83297333 -3.12888386 -9.83622621 -2.86441068 -2.81665608 -5.08312498
-4.13873784 -3.38146656 -2.44281115]
Best objective: 316.27366167454034
Mean objective: 574.0955045882748
Inner objective at best sample: 4194452.033315194
Gradient objective at best sample: 0.04194135759653519
Time elapsed: 176.54947113990784
Iteration: 27
Best parameters: [ -5.48209517 -2.76632581 -10.50294842 -2.68850879 -2.35496124
-4.84125884 -4.2978495 -3.69001994 -1.97789981]
Best objective: 290.3418219022524
Mean objective: 546.2055881311051
Inner objective at best sample: 337048.8262697556
Gradient objective at best sample: 0.0033675848444785334
Time elapsed: 188.73575520515442
Iteration: 28
Best parameters: [ -5.86537891 -3.16555922 -10.20221841 -2.76481214 -2.41482663
-5.16574202 -3.6536854 -3.52293066 -2.49842721]
Best objective: 263.59015531269023
Mean objective: 487.33150528675367
Inner objective at best sample: 3410331.34389459
Gradient objective at best sample: 0.03410067753739277
Time elapsed: 162.70864939689636
Iteration: 29
Best parameters: [-5.92013914 -3.07286508 -9.91357081 -2.78107309 -2.29631265 -4.97450263
-3.35442081 -3.36807204 -2.59663501]
Best objective: 237.20299755841046
Mean objective: 430.4091044118624
Inner objective at best sample: 19418593.893140685
Gradient objective at best sample: 0.19418356690143126
Time elapsed: 185.31618213653564
Iteration: 30
Best parameters: [ -5.75473793 -2.83496238 -10.15660307 -2.78504288 -2.6114547
-5.02047639 -3.85400703 -3.47697304 -2.43967103]
Best objective: 247.82176150064666
Mean objective: 432.6319097861177
Inner objective at best sample: 3106713.5923011727
Gradient objective at best sample: 0.03106465770539672
Time elapsed: 170.91355562210083
Iteration: 31
Best parameters: [ -5.49415911 -2.95772664 -10.26216411 -2.71589817 -2.45084324
-4.87026385 -3.5949448 -3.52665415 -2.54401921]
Best objective: 221.901840167979
Mean objective: 375.49800458908686
Inner objective at best sample: 4054029.915838285
Gradient objective at best sample: 0.04053808013998117
Time elapsed: 157.2279269695282
Iteration: 32
Best parameters: [ -5.49457459 -2.91247577 -10.18424396 -2.76558684 -2.3371337
-5.1062598 -3.58355772 -3.50399387 -2.49907825]
Best objective: 215.0804814319256
Mean objective: 298.35878808788544
Inner objective at best sample: 5510527.183157255
Gradient objective at best sample: 0.055103121026758226
Time elapsed: 166.9434289932251
Iteration: 33
Best parameters: [-5.73694353 -2.88078806 -9.99868246 -2.8016871 -2.27736647 -4.91002359
-3.30141915 -3.38584499 -2.5930743 ]
Best objective: 201.8474628909617
Mean objective: 286.8874587707648
Inner objective at best sample: 19349525.816330187
Gradient objective at best sample: 0.19349323968867294
Time elapsed: 184.63901710510254
Iteration: 34
Best parameters: [ -5.32700752 -2.6234936 -10.62473202 -2.64949585 -2.22944143
-4.86233596 -3.40241398 -3.48963288 -2.5295994 ]
Best objective: 205.0889847092135
Mean objective: 265.8403304569139
Inner objective at best sample: 10963328.329458917
Gradient objective at best sample: 0.10963123240474207
Time elapsed: 191.52377891540527
Iteration: 35
Best parameters: [-5.46308867 -2.92705109 -9.99390757 -2.80515515 -2.03435083 -5.2617503
-2.97028317 -3.3339762 -2.66926099]
Best objective: 196.57355561738282
Mean objective: 265.2704013113083
Inner objective at best sample: 15508907.412721459
Gradient objective at best sample: 0.15508710839165843
Time elapsed: 221.1514081954956
Iteration: 36
Best parameters: [ -5.52242142 -2.78145758 -10.16457359 -2.79175139 -2.11507285
-5.03057002 -2.93506945 -3.36170278 -2.75636443]
Best objective: 179.2828717596006
Mean objective: 246.77783976738803
Inner objective at best sample: 16301064.644737545
Gradient objective at best sample: 0.16300885361865786
Time elapsed: 229.85313653945923
Iteration: 37
Best parameters: [ -5.52813377 -2.74431251 -10.31610762 -2.78921132 -1.9155539
-4.80243643 -2.56847433 -3.28905882 -2.87105646]
Best objective: 191.05279231286792
Mean objective: 278.3262616229493
Inner objective at best sample: 46307438.753853716
Gradient objective at best sample: 0.46307247701061405
Time elapsed: 265.48759937286377
Iteration: 38
Best parameters: [ -5.52366194 -2.75643792 -10.36561049 -2.76116395 -1.79583323
-4.79285525 -2.44728363 -3.43499596 -2.84083784]
Best objective: 214.30294718704783
Mean objective: 333.56046062685044
Inner objective at best sample: 15204541.553175936
Gradient objective at best sample: 0.15204327250228747
Time elapsed: 272.2982943058014
Iteration: 39
Best parameters: [ -5.36142395 -2.69904079 -10.29172667 -2.73686369 -1.66033535
-5.17175773 -2.50232503 -3.34608811 -2.76246583]
Best objective: 176.95918554726342
Mean objective: 258.7355624004062
Inner objective at best sample: 15715345.408958208
Gradient objective at best sample: 0.1571516844977266
Time elapsed: 276.3172459602356
Iteration: 40
Best parameters: [-5.18389677 -2.59021445 -9.99310542 -2.83452068 -1.71229983 -4.61407984
-2.38805623 -3.36928167 -2.84406232]
Best objective: 174.15936427663314
Mean objective: 232.94690058349582
Inner objective at best sample: 19823622.934284806
Gradient objective at best sample: 0.19823448774920532
Time elapsed: 284.87278866767883
Iteration: 41
Best parameters: [ -5.3383698 -2.7326779 -10.01425599 -2.85337067 -1.7675583
-4.72228284 -2.53519504 -3.41587946 -2.77989033]
Best objective: 169.2276455680061
Mean objective: 224.1089192179754
Inner objective at best sample: 15646023.797391687
Gradient objective at best sample: 0.15645854569746118
Time elapsed: 301.94226121902466
Iteration: 42
Best parameters: [-5.30017631 -2.80273413 -9.54820802 -2.93245872 -1.74491317 -5.11476341
-2.65042873 -3.34584651 -2.70773677]
Best objective: 174.08904770142064
Mean objective: 201.99582866548357
Inner objective at best sample: 14305939.426684227
Gradient objective at best sample: 0.14305765337636525
Time elapsed: 293.2024071216583
Iteration: 43
Best parameters: [ -5.09351757 -2.56060877 -10.13072596 -2.80937958 -1.72044535
-4.94409295 -2.50830005 -3.32127884 -2.78587886]
Best objective: 167.5105327047271
Mean objective: 190.0330926681232
Inner objective at best sample: 23663718.3039731
Gradient objective at best sample: 0.23663550793440397
Time elapsed: 303.40089106559753
Iteration: 44
Best parameters: [-5.23241707 -2.68429992 -9.891885 -2.8453765 -1.55033562 -5.20921359
-2.51631201 -3.35156815 -2.66515956]
Best objective: 157.95487156984655
Mean objective: 183.38801744603774
Inner objective at best sample: 15065016.4288543
Gradient objective at best sample: 0.15064858473982728
Time elapsed: 296.406197309494
Iteration: 45
Best parameters: [ -5.26166705 -2.67982168 -10.03402069 -2.82888166 -1.53237473
-4.87183451 -2.36309936 -3.37807118 -2.75273064]
Best objective: 158.99743134729374
Mean objective: 180.05962598514876
Inner objective at best sample: 17370986.020555615
Gradient objective at best sample: 0.17370827023124266
Time elapsed: 315.72465443611145
Iteration: 46
Best parameters: [-5.12366961 -2.58964656 -9.84185443 -2.87407214 -1.35719244 -5.23314633
-2.31771361 -3.3549538 -2.66983039]
Best objective: 159.02128981640666
Mean objective: 174.6296547433991
Inner objective at best sample: 25063616.060373187
Gradient objective at best sample: 0.2506345703908337
Time elapsed: 343.5190396308899
Iteration: 47
Best parameters: [-5.24466593 -2.65133811 -9.98981187 -2.8566183 -1.17710383 -5.10506203
-1.97556322 -3.31394584 -2.77589008]
Best objective: 163.0504007522261
Mean objective: 183.57067390355783
Inner objective at best sample: 116195842.12823434
Gradient objective at best sample: 1.161956790778336
Time elapsed: 308.7689907550812
Iteration: 48
Best parameters: [-5.16820147 -2.64752309 -9.72612483 -2.87910229 -1.52340322 -5.15215001
-2.44936296 -3.36101015 -2.6840107 ]
Best objective: 163.49640683319444
Mean objective: 178.62455711663773
Inner objective at best sample: 15396499.587886656
Gradient objective at best sample: 0.15396336091479823
Time elapsed: 309.7100772857666
Iteration: 49
Best parameters: [ -5.12437692 -2.59691445 -10.08308303 -2.79664539 -1.25053363
-4.88630932 -2.32468408 -3.46670107 -2.60253172]
Best objective: 156.02500386485553
Mean objective: 175.36470490244764
Inner objective at best sample: 18127291.90714508
Gradient objective at best sample: 0.18127135882141213
Time elapsed: 311.7802565097809
Iteration: 50
Best parameters: [ -5.14135746 -2.59255855 -10.10224358 -2.80996038 -1.3811917
-4.81889668 -2.35595184 -3.45123611 -2.67136588]
Best objective: 155.2973395455812
Mean objective: 170.32747201602308
Inner objective at best sample: 17294987.046114493
Gradient objective at best sample: 0.17294831748774947
Time elapsed: 322.2660059928894
Iteration: 51
Best parameters: [ -4.97162151 -2.49984064 -10.12533437 -2.81702242 -1.14203286
-4.90359097 -2.11605765 -3.43293122 -2.67913584]
Best objective: 157.99277492197925
Mean objective: 165.50367591290333
Inner objective at best sample: 20101249.185968515
Gradient objective at best sample: 0.20101091193193593
Time elapsed: 360.70705580711365
Iteration: 52
Best parameters: [ -5.07342835 -2.57806967 -10.0257464 -2.82469919 -1.12736997
-5.08291852 -2.07080969 -3.37737501 -2.6888065 ]
Best objective: 156.63804850430085
Mean objective: 163.73336857970043
Inner objective at best sample: 40729236.14022983
Gradient objective at best sample: 0.4072907950218132
Time elapsed: 347.4402208328247
Iteration: 53
Best parameters: [ -5.16646089 -2.61394371 -10.10188202 -2.81982024 -1.29479986
-4.67649561 -2.20555486 -3.45504549 -2.72310671]
Best objective: 157.35585571332444
Mean objective: 161.53126536447678
Inner objective at best sample: 17547121.378937595
Gradient objective at best sample: 0.17546964023081882
Time elapsed: 350.610315322876
Iteration: 54
Best parameters: [ -5.13456557 -2.6226933 -10.09947685 -2.8053324 -1.5512567
-4.74187553 -2.56490959 -3.47395702 -2.64400033]
Best objective: 156.63071179191624
Mean objective: 160.6400192219556
Inner objective at best sample: 18821549.26380317
Gradient objective at best sample: 0.1882139263309138
Time elapsed: 316.8795166015625
Iteration: 55
Best parameters: [-5.13351376 -2.59001096 -9.91254076 -2.85326161 -1.24656805 -4.71428397
-2.20572762 -3.45384827 -2.67563243]
Best objective: 155.71524967009438
Mean objective: 160.64172981402768
Inner objective at best sample: 17907360.590152312
Gradient objective at best sample: 0.17907204874902644
Time elapsed: 320.94970512390137
Iteration: 56
Best parameters: [ -5.15253637 -2.59759235 -10.05655245 -2.81139073 -1.39757086
-4.65186802 -2.38840869 -3.47828047 -2.65884524]
Best objective: 154.9508597210127
Mean objective: 159.54899812321028
Inner objective at best sample: 18354978.488265764
Gradient objective at best sample: 0.18354823537406043
Time elapsed: 332.83947229385376
Iteration: 57
Best parameters: [ -5.07932668 -2.56236918 -10.14596977 -2.80087212 -1.28973364
-4.5603648 -2.24222562 -3.49343257 -2.69314782]
Best objective: 155.81513048307738
Mean objective: 159.28862704701118
Inner objective at best sample: 18774931.982833765
Gradient objective at best sample: 0.1877477616770328
Time elapsed: 355.50462675094604
Iteration: 58
Best parameters: [ -5.0745174 -2.57727607 -10.08260523 -2.81241035 -1.37515141
-4.69710134 -2.3743101 -3.48770938 -2.65975374]
Best objective: 155.20261508080966
Mean objective: 158.16254625575175
Inner objective at best sample: 18640530.61504115
Gradient objective at best sample: 0.1864037541242607
Time elapsed: 313.1555366516113
Iteration: 59
Best parameters: [ -5.06078262 -2.5623117 -10.12709043 -2.795003 -1.30108807
-4.47477188 -2.28748569 -3.53886842 -2.66562458]
Best objective: 154.98931455683493
Mean objective: 156.842500899105
Inner objective at best sample: 20432840.43821449
Gradient objective at best sample: 0.20432685448899932
Time elapsed: 297.57453179359436
Iteration: 60
Best parameters: [ -5.07554997 -2.576939 -10.03517892 -2.82982995 -1.30775062
-4.63099249 -2.22153215 -3.47403299 -2.71169551]
Best objective: 154.7482858543886
Mean objective: 156.46272101791206
Inner objective at best sample: 17981196.053548392
Gradient objective at best sample: 0.17981041305262535
Time elapsed: 289.7387590408325
Iteration: 61
Best parameters: [ -5.1315168 -2.60988513 -10.07442775 -2.81319058 -1.31517943
-4.6009524 -2.2539703 -3.4846695 -2.69373509]
Best objective: 154.61161504439832
Mean objective: 155.60972631716643
Inner objective at best sample: 18204781.287655637
Gradient objective at best sample: 0.18204626676040594
Time elapsed: 297.9385623931885
Iteration: 62
Best parameters: [ -5.13965302 -2.59696994 -10.07977083 -2.81335521 -1.40002384
-4.64820113 -2.34877855 -3.47684167 -2.68509304]
Best objective: 154.4819405059515
Mean objective: 155.48044506641114
Inner objective at best sample: 18027896.277656086
Gradient objective at best sample: 0.18027741795715582
Time elapsed: 289.75841331481934
Iteration: 63
Best parameters: [ -5.13590605 -2.59310013 -10.00218056 -2.82387252 -1.34779638
-4.68238377 -2.34664792 -3.47613239 -2.65078241]
Best objective: 154.40782858117782
Mean objective: 154.9041910125328
Inner objective at best sample: 18228184.999602865
Gradient objective at best sample: 0.18228030591774286
Time elapsed: 300.86007833480835
Iteration: 64
Best parameters: [ -5.14613421 -2.60209676 -10.0309701 -2.81682496 -1.34820003
-4.70673095 -2.33869428 -3.47204535 -2.6559215 ]
Best objective: 154.34153518838085
Mean objective: 154.78702882981725
Inner objective at best sample: 17999503.175706062
Gradient objective at best sample: 0.17999348834170872
Time elapsed: 296.02946853637695
Iteration: 65
Best parameters: [ -5.07463498 -2.56270055 -10.06988719 -2.81607072 -1.31909918
-4.61471979 -2.29421663 -3.49506005 -2.67203256]
Best objective: 154.37163584115262
Mean objective: 154.8981626628815
Inner objective at best sample: 18812418.91675004
Gradient objective at best sample: 0.18812264545114202
Time elapsed: 301.85809087753296
Iteration: 66
Best parameters: [ -5.09993698 -2.58427825 -10.05165437 -2.81762054 -1.33835558
-4.64679273 -2.30302969 -3.47550782 -2.67807219]
Best objective: 154.3255519796063
Mean objective: 154.6988581717557
Inner objective at best sample: 18127643.117177803
Gradient objective at best sample: 0.18127488791625823
Time elapsed: 290.24471282958984
Iteration: 67
Best parameters: [ -5.10771204 -2.58578928 -10.00125169 -2.83134987 -1.34761394
-4.66315067 -2.30932331 -3.47165517 -2.67603144]
Best objective: 154.22828316838869
Mean objective: 154.5522891191164
Inner objective at best sample: 17973277.758310903
Gradient objective at best sample: 0.17973123530027738
Time elapsed: 292.9428105354309
Iteration: 68
Best parameters: [ -5.10151759 -2.58279019 -10.07554943 -2.81270864 -1.31627646
-4.60933414 -2.29043014 -3.49578253 -2.6693709 ]
Best objective: 154.12400219275784
Mean objective: 154.37660796978878
Inner objective at best sample: 18745004.592137348
Gradient objective at best sample: 0.18744850468135157
Time elapsed: 301.38931155204773
Iteration: 69
Best parameters: [ -5.0954714 -2.58829844 -10.02021727 -2.82728981 -1.32165337
-4.60302584 -2.28849979 -3.4964455 -2.67513573]
Best objective: 154.17664266121665
Mean objective: 154.37646645761018
Inner objective at best sample: 18718547.341826685
Gradient objective at best sample: 0.18718393165184025
Time elapsed: 300.55989956855774
Iteration: 70
Best parameters: [ -5.11461258 -2.59400985 -10.02071124 -2.82441717 -1.34105237
-4.63978911 -2.29562378 -3.47734887 -2.68006006]
Best objective: 154.24745147370817
Mean objective: 154.4013011549377
Inner objective at best sample: 18082409.931645494
Gradient objective at best sample: 0.1808225568419402
Time elapsed: 294.164475440979
Iteration: 71
Best parameters: [ -5.09774205 -2.57902961 -10.01285039 -2.83010518 -1.32139085
-4.59569129 -2.28004199 -3.49436739 -2.67803732]
Best objective: 154.13484140225734
Mean objective: 154.3402952712742
Inner objective at best sample: 18659205.66245973
Gradient objective at best sample: 0.1865905152761833
Time elapsed: 287.8830373287201
Iteration: 72
Best parameters: [ -5.101446 -2.58179646 -10.03351648 -2.82219239 -1.3356447
-4.6060449 -2.30646565 -3.49669301 -2.67023763]
Best objective: 154.1521720000227
Mean objective: 154.29199545400343
Inner objective at best sample: 18772876.267094564
Gradient objective at best sample: 0.18772722114922563
Time elapsed: 290.5994699001312
Iteration: 73
Best parameters: [ -5.09404834 -2.58158225 -10.02026548 -2.82435867 -1.32550168
-4.58793394 -2.29461668 -3.49891932 -2.67044285]
Best objective: 154.13152231196392
Mean objective: 154.2753164151691
Inner objective at best sample: 18858147.59480131
Gradient objective at best sample: 0.18857993463279
Time elapsed: 290.5923638343811
Iteration: 74
Best parameters: [ -5.10665191 -2.58563643 -10.01866661 -2.82566812 -1.34943411
-4.59296811 -2.31629973 -3.49786883 -2.67281224]
Best objective: 154.01626825938317
Mean objective: 154.23359093642847
Inner objective at best sample: 18808433.800096206
Gradient objective at best sample: 0.18808279783827944
Time elapsed: 287.75077962875366
Iteration: 75
Best parameters: [ -5.09666213 -2.58339822 -10.00735219 -2.82686115 -1.33349271
-4.58206501 -2.29765026 -3.49744025 -2.67450708]
Best objective: 154.05457039073968
Mean objective: 154.23050685778372
Inner objective at best sample: 18803353.96708596
Gradient objective at best sample: 0.1880319991251557
Time elapsed: 297.25730061531067
Iteration: 76
Best parameters: [ -5.11153137 -2.59017334 -10.01431396 -2.82728264 -1.36279314
-4.60677902 -2.32282863 -3.48822143 -2.67723147]
Best objective: 154.0691997123206
Mean objective: 154.21466012776324
Inner objective at best sample: 18480037.26005299
Gradient objective at best sample: 0.18479883190853277
Time elapsed: 286.86989164352417
Iteration: 77
Best parameters: [ -5.1066229 -2.5937304 -10.02240747 -2.82325674 -1.33432829
-4.59944678 -2.30754581 -3.4965941 -2.67055338]
Best objective: 154.08296582739783
Mean objective: 154.20954865928164
Inner objective at best sample: 18762554.241097
Gradient objective at best sample: 0.1876240015813117
Time elapsed: 296.05869579315186
Iteration: 78
Best parameters: [ -5.10184936 -2.58484826 -10.01407375 -2.82649998 -1.34312432
-4.61367533 -2.31158033 -3.49082212 -2.67226326]
Best objective: 154.05669399904664
Mean objective: 154.19243856149768
Inner objective at best sample: 18587467.394698124
Gradient objective at best sample: 0.18587313338004127
Time elapsed: 293.9164264202118
Iteration: 79
Best parameters: [ -5.10738724 -2.58738414 -10.01136267 -2.82725866 -1.33812831
-4.59684335 -2.30762659 -3.4955545 -2.67204066]
Best objective: 154.02401459479424
Mean objective: 154.1676770713001
Inner objective at best sample: 18737146.296879742
Gradient objective at best sample: 0.18736992272865147
Time elapsed: 290.95924067497253
Iteration: 80
Best parameters: [ -5.09590025 -2.58213322 -10.03471054 -2.82030911 -1.33003868
-4.58887805 -2.3018253 -3.49983373 -2.6705362 ]
Best objective: 153.97009580590998
Mean objective: 154.1312920718146
Inner objective at best sample: 18900249.3265002
Gradient objective at best sample: 0.18900095356404395
Time elapsed: 294.78149008750916
Iteration: 81
Best parameters: [ -5.09812835 -2.58407621 -10.02291845 -2.82259604 -1.33497928
-4.59807616 -2.30855861 -3.49630305 -2.66938853]
Best objective: 153.9919535886313
Mean objective: 154.11665498171627
Inner objective at best sample: 18795459.536321007
Gradient objective at best sample: 0.18795305544367416
Time elapsed: 287.9129753112793
Iteration: 82
Best parameters: [ -5.09971722 -2.58393591 -10.02703489 -2.82390251 -1.32364111
-4.58059335 -2.29185355 -3.50058977 -2.673041 ]
Best objective: 153.96499122612954
Mean objective: 154.14296727479262
Inner objective at best sample: 18897867.563761886
Gradient objective at best sample: 0.1889771359877066
Time elapsed: 289.2051899433136
Iteration: 83
Best parameters: [ -5.10105301 -2.58591208 -10.02899836 -2.82087268 -1.33299773
-4.60655157 -2.30765784 -3.49385253 -2.66801595]
Best objective: 154.00238628840657
Mean objective: 154.13303469323125
Inner objective at best sample: 18712438.19697863
Gradient objective at best sample: 0.1871228419459234
Time elapsed: 289.5101811885834
Iteration: 84
Best parameters: [ -5.09982815 -2.58026843 -10.028697 -2.82318484 -1.32212114
-4.57500732 -2.29514569 -3.50290931 -2.66970254]
Best objective: 154.03503807268186
Mean objective: 154.13201064097862
Inner objective at best sample: 19015234.94304128
Gradient objective at best sample: 0.19015080908003207
Time elapsed: 287.50970482826233
Iteration: 85
Best parameters: [ -5.10343199 -2.58532596 -10.00689086 -2.82617127 -1.3244865
-4.59461479 -2.3000884 -3.49747491 -2.66710008]
Best objective: 153.98547786675022
Mean objective: 154.11797931355554
Inner objective at best sample: 18828481.914730586
Gradient objective at best sample: 0.1882832792925272
Time elapsed: 287.1243095397949
Iteration: 86
Best parameters: [ -5.10055956 -2.58207927 -10.02369947 -2.82292328 -1.33364413
-4.59172148 -2.30533774 -3.49858057 -2.66963398]
Best objective: 154.01027490572056
Mean objective: 154.1182378714973
Inner objective at best sample: 18860692.787143093
Gradient objective at best sample: 0.18860538776868188
Time elapsed: 288.6928164958954
Iteration: 87
Best parameters: [ -5.09208254 -2.57900641 -10.02513663 -2.82365205 -1.32000574
-4.585093 -2.29514813 -3.50090277 -2.66846697]
Best objective: 153.999138734858
Mean objective: 154.12127906165287
Inner objective at best sample: 18962726.77777596
Gradient objective at best sample: 0.1896257277863722
Time elapsed: 289.35414719581604
Iteration: 88
Best parameters: [ -5.10544171 -2.5862581 -10.02096167 -2.82306249 -1.32794833
-4.58052838 -2.30118127 -3.50103434 -2.66929282]
Best objective: 154.00182103731487
Mean objective: 154.10519764429137
Inner objective at best sample: 18940452.59935223
Gradient objective at best sample: 0.1894029859753119
Time elapsed: 298.03392577171326
Iteration: 89
Best parameters: [ -5.10529158 -2.58552958 -10.02386106 -2.82249676 -1.33167979
-4.59831507 -2.30560507 -3.49633099 -2.66865444]
Best objective: 153.99491035775185
Mean objective: 154.1221279325824
Inner objective at best sample: 18783760.499957792
Gradient objective at best sample: 0.18783606505047432
Time elapsed: 292.21735739707947
Iteration: 90
Best parameters: [ -5.10993645 -2.58913303 -10.03227273 -2.82050271 -1.33378949
-4.59870945 -2.30647601 -3.49669146 -2.6695654 ]
Best objective: 154.00449365284027
Mean objective: 154.1047324949259
Inner objective at best sample: 18771658.20012498
Gradient objective at best sample: 0.18771504195631325
Time elapsed: 286.0254912376404
Iteration: 91
Best parameters: [ -5.1005622 -2.58330199 -10.03186304 -2.82109379 -1.32593538
-4.59313956 -2.2983037 -3.4987125 -2.66997843]
Best objective: 153.98628348081454
Mean objective: 154.0821732987693
Inner objective at best sample: 18851486.932199482
Gradient objective at best sample: 0.18851332945916002
Time elapsed: 292.3775851726532
Iteration: 92
Best parameters: [ -5.0977731 -2.58311819 -10.02472066 -2.82333524 -1.32350019
-4.58442412 -2.29573564 -3.50116138 -2.67021494]
Best objective: 153.9632276402986
Mean objective: 154.0827233720082
Inner objective at best sample: 18936918.263960086
Gradient objective at best sample: 0.18936764300732445
Time elapsed: 295.5583884716034
Iteration: 93
Best parameters: [ -5.1004004 -2.58283541 -10.02628212 -2.82339903 -1.33296727
-4.5891819 -2.30267265 -3.49986095 -2.67176809]
Best objective: 153.99517467352555
Mean objective: 154.08224948893277
Inner objective at best sample: 18881120.49660276
Gradient objective at best sample: 0.18880966501428087
Time elapsed: 288.65546798706055
Iteration: 94
Best parameters: [ -5.10170112 -2.58324974 -10.0263103 -2.82308813 -1.32894344
-4.58468885 -2.30019383 -3.50078036 -2.67049861]
Best objective: 153.97211242252217
Mean objective: 154.0749167226215
Inner objective at best sample: 18921072.11016541
Gradient objective at best sample: 0.1892091813805299
Time elapsed: 289.73441314697266
Iteration: 95
Best parameters: [ -5.10114266 -2.58333337 -10.02561741 -2.82344643 -1.32545692
-4.58497832 -2.29768059 -3.50076292 -2.66983772]
Best objective: 153.96874745401396
Mean objective: 154.05203983510697
Inner objective at best sample: 18921935.71986366
Gradient objective at best sample: 0.18921781751116204
Time elapsed: 295.2701156139374
Iteration: 96
Best parameters: [ -5.10154853 -2.58342325 -10.02631731 -2.82281957 -1.32479901
-4.57536794 -2.29581121 -3.50287656 -2.67083841]
Best objective: 153.983505571108
Mean objective: 154.06739736078822
Inner objective at best sample: 18991478.626998585
Gradient objective at best sample: 0.18991324643493016
Time elapsed: 289.3881678581238
Iteration: 97
Best parameters: [ -5.1048408 -2.58526472 -10.02451598 -2.82281303 -1.32986871
-4.58611749 -2.30195962 -3.50002357 -2.66978018]
Best objective: 153.97258376723323
Mean objective: 154.0398538957642
Inner objective at best sample: 18896562.487082977
Gradient objective at best sample: 0.1889640851449921
Time elapsed: 294.897132396698
Iteration: 98
Best parameters: [ -5.09945788 -2.58296107 -10.0288576 -2.82250431 -1.32373132
-4.58855995 -2.29542669 -3.50018547 -2.670548 ]
Best objective: 153.95986262910233
Mean objective: 154.04265145767837
Inner objective at best sample: 18896852.09442395
Gradient objective at best sample: 0.18896698134561318
Time elapsed: 288.52549386024475
Iteration: 99
Best parameters: [ -5.09930353 -2.58268823 -10.02585809 -2.82330514 -1.322328
-4.58092762 -2.29253232 -3.502158 -2.67158967]
Best objective: 153.9422031273609
Mean objective: 154.0194738471724
Inner objective at best sample: 18954569.98843999
Gradient objective at best sample: 0.18954416046236863
Time elapsed: 286.6698091030121
Iteration: 100
Best parameters: [ -5.09933894 -2.5822941 -10.02648761 -2.8233611 -1.32184155
-4.58362021 -2.29317984 -3.50136022 -2.67082434]
Best objective: 153.95216162138448
Mean objective: 154.0211591760736
Inner objective at best sample: 18937883.644853044
Gradient objective at best sample: 0.1893772969269142
Time elapsed: 287.770140171051
Iteration: 101
Best parameters: [ -5.09839348 -2.58118334 -10.02298776 -2.82412897 -1.31969428
-4.57785606 -2.29147342 -3.50254003 -2.6703196 ]
Best objective: 153.95412625175766
Mean objective: 154.03095953276653
Inner objective at best sample: 18987954.75548793
Gradient objective at best sample: 0.18987800801361682
Time elapsed: 295.422488451004
Iteration: 102
Best parameters: [ -5.10032754 -2.58383848 -10.02939406 -2.82274502 -1.32634218
-4.5862696 -2.29680447 -3.50067314 -2.6715214 ]
Best objective: 153.9410862416224
Mean objective: 154.04065975320114
Inner objective at best sample: 18904803.862771753
Gradient objective at best sample: 0.18904649921685512
Time elapsed: 287.42036390304565
Iteration: 103
Best parameters: [ -5.10305407 -2.58465523 -10.02264792 -2.82398665 -1.3281328
-4.58634309 -2.29907411 -3.5001564 -2.67097689]
Best objective: 153.9239706740606
Mean objective: 154.0181477575625
Inner objective at best sample: 18892375.3238287
Gradient objective at best sample: 0.18892221399858028
Time elapsed: 290.93307399749756
Iteration: 104
Best parameters: [ -5.10025805 -2.58293179 -10.0283101 -2.82292579 -1.32637892
-4.59108376 -2.29697463 -3.49927193 -2.67137446]
Best objective: 153.9660281268265
Mean objective: 154.03454060548492
Inner objective at best sample: 18860666.315308277
Gradient objective at best sample: 0.18860512349280148
Time elapsed: 286.7070472240448
Iteration: 105
Best parameters: [ -5.09875244 -2.58268708 -10.02952668 -2.82274657 -1.32660326
-4.58707177 -2.29706493 -3.50071492 -2.6714916 ]
Best objective: 153.96208986260126
Mean objective: 154.02886854608153
Inner objective at best sample: 18909585.65055405
Gradient objective at best sample: 0.18909431688464187
Time elapsed: 295.07645082473755
Iteration: 106
Best parameters: [ -5.10042964 -2.58282054 -10.02484029 -2.8238623 -1.32371281
-4.58124773 -2.29422109 -3.50201103 -2.6713775 ]
Best objective: 153.96034670089776
Mean objective: 154.01318533765144
Inner objective at best sample: 18950726.061223425
Gradient objective at best sample: 0.18950572100876723
Time elapsed: 289.4909818172455
Iteration: 107
Best parameters: [ -5.0996467 -2.58198 -10.02861676 -2.82325376 -1.32382403
-4.58298813 -2.29482426 -3.50163694 -2.67141695]
Best objective: 153.96099363631942
Mean objective: 154.0261805413403
Inner objective at best sample: 18944813.534836736
Gradient objective at best sample: 0.189446595738431
Time elapsed: 288.7279715538025
Iteration: 108
Best parameters: [ -5.09757296 -2.58085192 -10.02744779 -2.82322053 -1.32097842
-4.58545648 -2.29359195 -3.50081865 -2.66992952]
Best objective: 153.96937686976827
Mean objective: 154.04592551601024
Inner objective at best sample: 18932312.290413383
Gradient objective at best sample: 0.18932158321036513
Time elapsed: 292.6444411277771
Iteration: 109
Best parameters: [ -5.10289277 -2.58401585 -10.02250295 -2.8239719 -1.32570911
-4.58990829 -2.29671048 -3.49941446 -2.67069403]
Best objective: 153.98797198557207
Mean objective: 154.04398278259234
Inner objective at best sample: 18864185.449953504
Gradient objective at best sample: 0.1886403146198152
Time elapsed: 285.3955671787262
Iteration: 110
Best parameters: [ -5.1010724 -2.58265284 -10.02530853 -2.82383246 -1.32596844
-4.5800842 -2.29629621 -3.50205053 -2.67146502]
Best objective: 153.93809232824051
Mean objective: 154.03936875207165
Inner objective at best sample: 18960061.76480893
Gradient objective at best sample: 0.18959907826716602
Time elapsed: 290.318430185318
Iteration: 111
Best parameters: [ -5.09889422 -2.5821144 -10.02813784 -2.82343604 -1.32192336
-4.58192987 -2.29183645 -3.50199022 -2.67198768]
Best objective: 153.92260625632366
Mean objective: 154.01681905429984
Inner objective at best sample: 18948109.359853767
Gradient objective at best sample: 0.18947955437247513
Time elapsed: 289.14287424087524
Iteration: 112
Best parameters: [ -5.09842443 -2.5816553 -10.02737109 -2.8233852 -1.32121068
-4.58080731 -2.29154321 -3.50221289 -2.67163939]
Best objective: 153.95819331994616
Mean objective: 154.0240988180771
Inner objective at best sample: 18960076.800986607
Gradient objective at best sample: 0.18959922842793286
Time elapsed: 293.61705136299133
Iteration: 113
Best parameters: [ -5.10104001 -2.58352773 -10.02673526 -2.8232406 -1.32561588
-4.58581091 -2.29573537 -3.50091702 -2.67169217]
Best objective: 153.93189645350122
Mean objective: 154.00861652558038
Inner objective at best sample: 18910458.925527357
Gradient objective at best sample: 0.18910304993630905
Time elapsed: 296.5250594615936
Iteration: 114
Best parameters: [ -5.10015485 -2.58322838 -10.02724921 -2.82306097 -1.32245879
-4.58624331 -2.2937904 -3.50078791 -2.6709073 ]
Best objective: 153.92458831553745
Mean objective: 154.01695627295138
Inner objective at best sample: 18911027.31166464
Gradient objective at best sample: 0.18910873387076327
Time elapsed: 293.9329891204834
Iteration: 115
Best parameters: [ -5.10130479 -2.58372994 -10.02626532 -2.82296357 -1.32258401
-4.58531356 -2.29437954 -3.50087817 -2.67048928]
Best objective: 153.93957638955015
Mean objective: 153.99848452528028
Inner objective at best sample: 18916955.60451859
Gradient objective at best sample: 0.18916801664942198
Time elapsed: 286.8993582725525
Iteration: 116
Best parameters: [ -5.099588 -2.58302777 -10.02641115 -2.82352566 -1.32066772
-4.58046399 -2.29074736 -3.50243701 -2.67162279]
Best objective: 153.94190534361007
Mean objective: 153.99561504180485
Inner objective at best sample: 18959713.223217607
Gradient objective at best sample: 0.18959559281312263
Time elapsed: 288.70773935317993
Iteration: 117
Best parameters: [ -5.09847547 -2.58217131 -10.02694417 -2.82336168 -1.32046699
-4.58233378 -2.29110036 -3.50192973 -2.67137068]
Best objective: 153.91153464923752
Mean objective: 154.00681804196242
Inner objective at best sample: 18949356.043450113
Gradient objective at best sample: 0.18949202131915466
Time elapsed: 284.1969668865204
Iteration: 118
Best parameters: [ -5.10012267 -2.58276489 -10.02446973 -2.82397331 -1.32090197
-4.58152404 -2.29175315 -3.50206005 -2.67107098]
Best objective: 153.93296909078447
Mean objective: 154.01122252962503
Inner objective at best sample: 18953129.420045543
Gradient objective at best sample: 0.18952975487076454
Time elapsed: 289.4458096027374
Iteration: 119
Best parameters: [ -5.10007204 -2.58297239 -10.02765058 -2.82311899 -1.32028742
-4.57796976 -2.29058976 -3.50298954 -2.67166258]
Best objective: 153.92867601964196
Mean objective: 153.99405953513147
Inner objective at best sample: 18980677.315883588
Gradient objective at best sample: 0.18980523387207568
Time elapsed: 292.8886239528656
Iteration: 120
Best parameters: [ -5.09976358 -2.58306912 -10.02667355 -2.82312751 -1.32163738
-4.58301289 -2.29259388 -3.50166915 -2.67102364]
Best objective: 153.94584352310193
Mean objective: 154.0003827974662
Inner objective at best sample: 18938766.76518178
Gradient objective at best sample: 0.18938612819338257
Time elapsed: 290.07226514816284
Iteration: 121
Best parameters: [ -5.10156179 -2.58394716 -10.02684687 -2.82309187 -1.32305717
-4.58380784 -2.29390498 -3.50143708 -2.67113538]
Best objective: 153.92959238378023
Mean objective: 154.00588494960138
Inner objective at best sample: 18928392.42510697
Gradient objective at best sample: 0.18928238495514588
Time elapsed: 293.081396818161
Iteration: 122
Best parameters: [ -5.09932821 -2.5827136 -10.02664199 -2.82348633 -1.32206118
-4.58277731 -2.29253639 -3.50181654 -2.67149879]
Best objective: 153.93478004992744
Mean objective: 153.99637600195285
Inner objective at best sample: 18942175.655870307
Gradient objective at best sample: 0.18942021721090258
Time elapsed: 294.68915271759033
Iteration: 123
Best parameters: [ -5.10026614 -2.58332564 -10.0266918 -2.82326706 -1.32121231
-4.58057682 -2.29186777 -3.502244 -2.67125353]
Best objective: 153.9164102362036
Mean objective: 153.99792960462673
Inner objective at best sample: 18958323.80956108
Gradient objective at best sample: 0.18958169893150845
Time elapsed: 288.40322279930115
Iteration: 124