iterations: 0 training error: 0.17784079363973077
iterations: 100 training error: 0.1706884503458128
iterations: 200 training error: 0.1684897105284339
iterations: 300 training error: 0.16631024454075297
iterations: 400 training error: 0.1638076119011462
iterations: 500 training error: 0.1607240285773778
iterations: 600 training error: 0.15896666175542534
iterations: 700 training error: 0.15767345795741405
iterations: 800 training error: 0.15667811107269364
iterations: 900 training error: 0.15593848281499037
iterations: 1000 training error: 0.15535673206526868
iterations: 1100 training error: 0.15487612262356495
iterations: 1200 training error: 0.15446854195914042
iterations: 1300 training error: 0.15411669125659797
iterations: 1400 training error: 0.15380801337065797
iterations: 1500 training error: 0.15353281130531124
iterations: 1600 training error: 0.15328341636223392
iterations: 1700 training error: 0.15305359400452775
iterations: 1800 training error: 0.1528379652131966
iterations: 1900 training error: 0.1526312032124404
iterations: 2000 training error: 0.15242634797395543
iterations: 2100 training error: 0.15221095317096536
iterations: 2200 training error: 0.15196987914367754
iterations: 2300 training error: 0.15171854312097627
iterations: 2400 training error: 0.15147787781055647
iterations: 2500 training error: 0.15124268664333307
iterations: 2600 training error: 0.1510021484945546
iterations: 2700 training error: 0.15074759093065632
iterations: 2800 training error: 0.15047439310237978
iterations: 2900 training error: 0.15018314505240352
iterations: 3000 training error: 0.14987932412094485
iterations: 3100 training error: 0.1495713035442873
iterations: 3200 training error: 0.1492676114502295
iterations: 3300 training error: 0.14897464164959628
iterations: 3400 training error: 0.1486955638693339
iterations: 3500 training error: 0.14843046729309303
iterations: 3600 training error: 0.14817723371829336
iterations: 3700 training error: 0.1479325518629724
iterations: 3800 training error: 0.14769274728449677
iterations: 3900 training error: 0.14745437731009245
iterations: 4000 training error: 0.14721464940827014
iterations: 4100 training error: 0.14697169999157836
iterations: 4200 training error: 0.14672471797534128
iterations: 4300 training error: 0.14647388583925008
iterations: 4400 training error: 0.14622015359319568
iterations: 4500 training error: 0.14596491315227564
iterations: 4600 training error: 0.1457096606995393
iterations: 4700 training error: 0.14545573940786136
iterations: 4800 training error: 0.14520421842936063
iterations: 4900 training error: 0.14495586771098704
iterations: 5000 training error: 0.14471117670288908
iterations: 5100 training error: 0.14447040294435676
iterations: 5200 training error: 0.1442336353020424
iterations: 5300 training error: 0.1440008566376212
iterations: 5400 training error: 0.14377199817079206
iterations: 5500 training error: 0.143546983021578
iterations: 5600 training error: 0.14332575878861845
iterations: 5700 training error: 0.14310831969656126
iterations: 5800 training error: 0.14289471875269882
iterations: 5900 training error: 0.1426850702384589
iterations: 6000 training error: 0.14247954318515957
iterations: 6100 training error: 0.1422783472949089
iterations: 6200 training error: 0.14208171373803474
iterations: 6300 training error: 0.1418898739075768
iterations: 6400 training error: 0.14170303920826907
iterations: 6500 training error: 0.14152138430103872
iterations: 6600 training error: 0.1413450351965432
iterations: 6700 training error: 0.14117406255762638
iterations: 6800 training error: 0.1410084797900402
iterations: 6900 training error: 0.14084824505772375
iterations: 7000 training error: 0.14069326620447448
iterations: 7100 training error: 0.14054340759648773
iterations: 7200 training error: 0.1403984980266503
iterations: 7300 training error: 0.14025833898020065
iterations: 7400 training error: 0.1401227127207382
iterations: 7500 training error: 0.13999138980231932
iterations: 7600 training error: 0.13986413574278508
iterations: 7700 training error: 0.13974071670378704
iterations: 7800 training error: 0.13962090411361502
iterations: 7900 training error: 0.13950447824008444
iterations: 8000 training error: 0.13939123077355814
iterations: 8100 training error: 0.13928096651655897
iterations: 8200 training error: 0.1391735042987901
iterations: 8300 training error: 0.1390686772472056
iterations: 8400 training error: 0.13896633254247265
iterations: 8500 training error: 0.13886633078787672
iterations: 8600 training error: 0.13876854510631312
iterations: 8700 training error: 0.1386728600671782
iterations: 8800 training error: 0.13857917052914612
iterations: 8900 training error: 0.13848738046830947
iterations: 9000 training error: 0.1383974018449942
iterations: 9100 training error: 0.1383091535475984
iterations: 9200 training error: 0.13822256043856343
iterations: 9300 training error: 0.1381375525163949
iterations: 9400 training error: 0.13805406419853378
iterations: 9500 training error: 0.13797203372270947
iterations: 9600 training error: 0.13789140265893576
iterations: 9700 training error: 0.13781211552021902
iterations: 9800 training error: 0.1377341194570684
iterations: 9900 training error: 0.13765736401883982
iterations: 10000 training error: 0.1375818009637588
iterations: 10100 training error: 0.13750738409926652
iterations: 10200 training error: 0.13743406913536924
iterations: 10300 training error: 0.13736181353627636
iterations: 10400 training error: 0.1372905763600291
iterations: 10500 training error: 0.13722031808201104
iterations: 10600 training error: 0.1371510004056739
iterations: 10700 training error: 0.13708258607137452
iterations: 10800 training error: 0.1370150386802217
iterations: 10900 training error: 0.1369483225525321
iterations: 11000 training error: 0.13688240263857962
iterations: 11100 training error: 0.1368172444927229
iterations: 11200 training error: 0.13675281431206754
iterations: 11300 training error: 0.1366890790302004
iterations: 11400 training error: 0.13662600644817535
iterations: 11500 training error: 0.13656356538105335
iterations: 11600 training error: 0.13650172579952924
iterations: 11700 training error: 0.13644045895148824
iterations: 11800 training error: 0.1363797374555514
iterations: 11900 training error: 0.13631953536551705
iterations: 12000 training error: 0.13625982820941943
iterations: 12100 training error: 0.1362005930091182
iterations: 12200 training error: 0.13614180828616843
iterations: 12300 training error: 0.13608345405807243
iterations: 12400 training error: 0.13602551182677017
iterations: 12500 training error: 0.1359679645591434
iterations: 12600 training error: 0.1359107966577863
iterations: 12700 training error: 0.13585399391944955
iterations: 12800 training error: 0.1357975434783582
iterations: 12900 training error: 0.13574143373186098
iterations: 13000 training error: 0.13568565424649595
iterations: 13100 training error: 0.1356301956434187
iterations: 13200 training error: 0.13557504946321908
iterations: 13300 training error: 0.13552020801139036
iterations: 13400 training error: 0.13546566418709324
iterations: 13500 training error: 0.13541141129929712
iterations: 13600 training error: 0.13535744287574422
iterations: 13700 training error: 0.1353037524713484
iterations: 13800 training error: 0.13525033348335982
iterations: 13900 training error: 0.13519717898078445
iterations: 14000 training error: 0.1351442815549881
iterations: 14100 training error: 0.13509163319713144
iterations: 14200 training error: 0.13503922520618475
iterations: 14300 training error: 0.1349870481289416
iterations: 14400 training error: 0.13493509173100487
iterations: 14500 training error: 0.13488334499544724
iterations: 14600 training error: 0.13483179614402643
iterations: 14700 training error: 0.13478043267465745
iterations: 14800 training error: 0.134729241408364
iterations: 14900 training error: 0.13467820853912343
iterations: 15000 training error: 0.13462731968073313
iterations: 15100 training error: 0.13457655990592504
iterations: 15200 training error: 0.13452591377421164
iterations: 15300 training error: 0.13447536534626678
iterations: 15400 training error: 0.1344248981839112
iterations: 15500 training error: 0.13437449533598173
iterations: 15600 training error: 0.13432413931159806
iterations: 15700 training error: 0.1342738120437649
iterations: 15800 training error: 0.1342234948481785
iterations: 15900 training error: 0.13417316838501503
iterations: 16000 training error: 0.13412281263612924
iterations: 16100 training error: 0.13407240691759556
iterations: 16200 training error: 0.13402192995959392
iterations: 16300 training error: 0.13397136010469293
iterations: 16400 training error: 0.13392067570483643
iterations: 16500 training error: 0.13386985584033836
iterations: 16600 training error: 0.1338188815427284
iterations: 16700 training error: 0.1337677377715123
iterations: 16800 training error: 0.1337164164447688
iterations: 16900 training error: 0.1336649207748381
iterations: 17000 training error: 0.13361327083282895
iterations: 17100 training error: 0.13356150934203617
iterations: 17200 training error: 0.1335097048361752
iterations: 17300 training error: 0.13345794671396732
iterations: 17400 training error: 0.13340632538541464
iterations: 17500 training error: 0.1333548951992886
iterations: 17600 training error: 0.13330363143213084
iterations: 17700 training error: 0.13325240739151029
iterations: 17800 training error: 0.13320101369550755
iterations: 17900 training error: 0.13314921291069504
iterations: 18000 training error: 0.1330967966397834
iterations: 18100 training error: 0.13304361668926062
iterations: 18200 training error: 0.13298958638013686
iterations: 18300 training error: 0.1329346648309657
iterations: 18400 training error: 0.13287883784060434
iterations: 18500 training error: 0.13282210249847665
iterations: 18600 training error: 0.13276445701814266
iterations: 18700 training error: 0.13270589464991475
iterations: 18800 training error: 0.13264639991699856
iterations: 18900 training error: 0.1325859455789786
iterations: 19000 training error: 0.13252448890454765
iterations: 19100 training error: 0.13246196565132182
iterations: 19200 training error: 0.1323982792906118
iterations: 19300 training error: 0.1323332809502303
iterations: 19400 training error: 0.13226673129225783
iterations: 19500 training error: 0.1321982278672904
iterations: 19600 training error: 0.13212707236450724
iterations: 19700 training error: 0.13205206499536656
iterations: 19800 training error: 0.13197134625154167
iterations: 19900 training error: 0.13188279159552257
iterations: 20000 training error: 0.1317854153985339
iterations: 20100 training error: 0.13168013342898077
iterations: 20200 training error: 0.13156807272932414
iterations: 20300 training error: 0.1314491917295461
iterations: 20400 training error: 0.13132266291752692
iterations: 20500 training error: 0.13118742227966018
iterations: 20600 training error: 0.1310423893816182
iterations: 20700 training error: 0.13088661564253626
iterations: 20800 training error: 0.13071945159544396
iterations: 20900 training error: 0.1305406226997148
iterations: 21000 training error: 0.13035010055504648
iterations: 21100 training error: 0.1301478987783934
iterations: 21200 training error: 0.12993407299844736
iterations: 21300 training error: 0.12970894614448997
iterations: 21400 training error: 0.1294733252390105
iterations: 21500 training error: 0.12922857562964207
iterations: 21600 training error: 0.12897658395660172
iterations: 21700 training error: 0.12871966160187054
iterations: 21800 training error: 0.12846040561325853
iterations: 21900 training error: 0.1282015253539088
iterations: 22000 training error: 0.1279456557224927
iterations: 22100 training error: 0.12769518771494182
iterations: 22200 training error: 0.1274521435328243
iterations: 22300 training error: 0.12721810894295132
iterations: 22400 training error: 0.12699421898692526
iterations: 22500 training error: 0.12678118250305656
iterations: 22600 training error: 0.12657932916155223
iterations: 22700 training error: 0.12638866720826372
iterations: 22800 training error: 0.12620894573732663
iterations: 22900 training error: 0.12603971832376404
iterations: 23000 training error: 0.12588040488186095
iterations: 23100 training error: 0.1257303477371777
iterations: 23200 training error: 0.1255888581155525
iterations: 23300 training error: 0.1254552509398452
iterations: 23400 training error: 0.12532886804577695
iterations: 23500 training error: 0.12520909161976365
iterations: 23600 training error: 0.12509535038803574
iterations: 23700 training error: 0.1249871210086553
iterations: 23800 training error: 0.12488392662248428
iterations: 23900 training error: 0.12478533393121576
iterations: 24000 training error: 0.12469094966586633
iterations: 24100 training error: 0.12460041694243779
iterations: 24200 training error: 0.12451341176325807
iterations: 24300 training error: 0.12442963978097006
iterations: 24400 training error: 0.12434883336475065
iterations: 24500 training error: 0.1242707489696516
iterations: 24600 training error: 0.12419516479275934
iterations: 24700 training error: 0.12412187869353174
iterations: 24800 training error: 0.12405070635425405
iterations: 24900 training error: 0.12398147965700548
iterations: 25000 training error: 0.12391404525447978
iterations: 25100 training error: 0.12384826331296728
iterations: 25200 training error: 0.12378400640665002
iterations: 25300 training error: 0.12372115854317027
iterations: 25400 training error: 0.12365961430122697
iterations: 25500 training error: 0.12359927806181881
iterations: 25600 training error: 0.12354006331566784
iterations: 25700 training error: 0.12348189203033386
iterations: 25800 training error: 0.12342469406152727
iterations: 25900 training error: 0.1233684065941651
iterations: 26000 training error: 0.12331297359980159
iterations: 26100 training error: 0.12325834529828046
iterations: 26200 training error: 0.1232044776129475
iterations: 26300 training error: 0.12315133161069204
iterations: 26400 training error: 0.12309887292070254
iterations: 26500 training error: 0.12304707112933548
iterations: 26600 training error: 0.1229958991530498
iterations: 26700 training error: 0.12294533259698541
iterations: 26800 training error: 0.12289534911316552
iterations: 26900 training error: 0.12284592777891414
iterations: 27000 training error: 0.12279704852190804
iterations: 27100 training error: 0.12274869162204793
iterations: 27200 training error: 0.1227008373206407
iterations: 27300 training error: 0.12265346556311044
iterations: 27400 training error: 0.12260655589215524
iterations: 27500 training error: 0.1225600874945611
iterations: 27600 training error: 0.1225140393886174
iterations: 27700 training error: 0.12246839072307569
iterations: 27800 training error: 0.12242312114601331
iterations: 27900 training error: 0.12237821119547133
iterations: 28000 training error: 0.12233364266465191
iterations: 28100 training error: 0.12228939890240098
iterations: 28200 training error: 0.12224546502266204
iterations: 28300 training error: 0.12220182801166751
iterations: 28400 training error: 0.12215847673581372
iterations: 28500 training error: 0.12211540186416431
iterations: 28600 training error: 0.1220725957261901
iterations: 28700 training error: 0.12203005212763024
iterations: 28800 training error: 0.12198776614609255
iterations: 28900 training error: 0.12194573392440185
iterations: 29000 training error: 0.1219039524750393
iterations: 29100 training error: 0.12186241950426238
iterations: 29200 training error: 0.12182113326034781
iterations: 29300 training error: 0.1217800924071645
iterations: 29400 training error: 0.12173929592202722
iterations: 29500 training error: 0.1216987430153929
iterations: 29600 training error: 0.12165843306928
iterations: 29700 training error: 0.12161836559108742
iterations: 29800 training error: 0.12157854017962283
iterations: 29900 training error: 0.12153895650045657
iterations: 30000 training error: 0.1214996142681083
iterations: 30100 training error: 0.12146051323298507
iterations: 30200 training error: 0.12142165317138076
iterations: 30300 training error: 0.12138303387719777
iterations: 30400 training error: 0.12134465515436148
iterations: 30500 training error: 0.1213065168091656
iterations: 30600 training error: 0.12126861864200472
iterations: 30700 training error: 0.12123096043814685
iterations: 30800 training error: 0.12119354195735572
iterations: 30900 training error: 0.12115636292230782
iterations: 31000 training error: 0.12111942300586345
iterations: 31100 training error: 0.12108272181734386
iterations: 31200 training error: 0.1210462588880435
iterations: 31300 training error: 0.12101003365626316
iterations: 31400 training error: 0.12097404545219381
iterations: 31500 training error: 0.12093829348300554
iterations: 31600 training error: 0.12090277681850758
iterations: 31700 training error: 0.12086749437773991
iterations: 31800 training error: 0.12083244491683875
iterations: 31900 training error: 0.12079762701848658
iterations: 32000 training error: 0.12076303908321612
iterations: 32100 training error: 0.12072867932278619
iterations: 32200 training error: 0.12069454575578832
iterations: 32300 training error: 0.12066063620558694
iterations: 32400 training error: 0.12062694830062759
iterations: 32500 training error: 0.12059347947708882
iterations: 32600 training error: 0.12056022698380091
iterations: 32700 training error: 0.12052718788929238
iterations: 32800 training error: 0.12049435909079115
iterations: 32900 training error: 0.12046173732496596
iterations: 33000 training error: 0.12042931918016553
iterations: 33100 training error: 0.12039710110989879
iterations: 33200 training error: 0.12036507944728721
iterations: 33300 training error: 0.12033325042022266
iterations: 33400 training error: 0.12030161016696733
iterations: 33500 training error: 0.12027015475194888
iterations: 33600 training error: 0.12023888018152162
iterations: 33700 training error: 0.12020778241948356
iterations: 33800 training error: 0.12017685740216909
iterations: 33900 training error: 0.12014610105295881
iterations: 34000 training error: 0.12011550929607481
iterations: 34100 training error: 0.12008507806956001
iterations: 34200 training error: 0.12005480333735999
iterations: 34300 training error: 0.12002468110045088
iterations: 34400 training error: 0.11999470740697851
iterations: 34500 training error: 0.11996487836139166
iterations: 34600 training error: 0.11993519013257095
iterations: 34700 training error: 0.11990563896096511
iterations: 34800 training error: 0.11987622116475974
iterations: 34900 training error: 0.11984693314511817
iterations: 35000 training error: 0.11981777139052988
iterations: 35100 training error: 0.11978873248032128
iterations: 35200 training error: 0.11975981308737808
iterations: 35300 training error: 0.11973100998013514
iterations: 35400 training error: 0.1197023200238896
iterations: 35500 training error: 0.11967374018149887
iterations: 35600 training error: 0.11964526751351438
iterations: 35700 training error: 0.11961689917781375
iterations: 35800 training error: 0.11958863242878034
iterations: 35900 training error: 0.11956046461608817
iterations: 36000 training error: 0.11953239318313888
iterations: 36100 training error: 0.11950441566519916
iterations: 36200 training error: 0.11947652968728481
iterations: 36300 training error: 0.11944873296183249
iterations: 36400 training error: 0.11942102328619668
iterations: 36500 training error: 0.11939339854000988
iterations: 36600 training error: 0.11936585668243692
iterations: 36700 training error: 0.11933839574935261
iterations: 36800 training error: 0.11931101385047095
iterations: 36900 training error: 0.11928370916644711
iterations: 37000 training error: 0.11925647994597524
iterations: 37100 training error: 0.11922932450289814
iterations: 37200 training error: 0.1192022412133465
iterations: 37300 training error: 0.11917522851292026
iterations: 37400 training error: 0.11914828489392179
iterations: 37500 training error: 0.11912140890265373
iterations: 37600 training error: 0.11909459913678619
iterations: 37700 training error: 0.11906785424279906
iterations: 37800 training error: 0.11904117291350699
iterations: 37900 training error: 0.11901455388566733
iterations: 38000 training error: 0.11898799593767265
iterations: 38100 training error: 0.11896149788733348
iterations: 38200 training error: 0.11893505858974543
iterations: 38300 training error: 0.11890867693524419
iterations: 38400 training error: 0.11888235184744836
iterations: 38500 training error: 0.1188560822813824
iterations: 38600 training error: 0.11882986722168644
iterations: 38700 training error: 0.11880370568090258
iterations: 38800 training error: 0.11877759669784056
iterations: 38900 training error: 0.11875153933601687
iterations: 39000 training error: 0.11872553268216673
iterations: 39100 training error: 0.11869957584482405
iterations: 39200 training error: 0.118673667952967
iterations: 39300 training error: 0.11864780815472682
iterations: 39400 training error: 0.11862199561615622
iterations: 39500 training error: 0.11859622952005341
iterations: 39600 training error: 0.11857050906484151
iterations: 39700 training error: 0.11854483346349869
iterations: 39800 training error: 0.11851920194253548
iterations: 39900 training error: 0.1184936137410183
iterations: 40000 training error: 0.11846806810963773
iterations: 40100 training error: 0.11844256430981548
iterations: 40200 training error: 0.11841710161285124
iterations: 40300 training error: 0.11839167929910642
iterations: 40400 training error: 0.11836629665722097
iterations: 40500 training error: 0.11834095298336625
iterations: 40600 training error: 0.11831564758052575
iterations: 40700 training error: 0.11829037975780667
iterations: 40800 training error: 0.1182651488297809
iterations: 40900 training error: 0.11823995411585098
iterations: 41000 training error: 0.11821479493964446
iterations: 41100 training error: 0.11818967062842976
iterations: 41200 training error: 0.11816458051255986
iterations: 41300 training error: 0.11813952392493489
iterations: 41400 training error: 0.11811450020049158
iterations: 41500 training error: 0.11808950867571137
iterations: 41600 training error: 0.1180645486881519
iterations: 41700 training error: 0.11803961957599936
iterations: 41800 training error: 0.11801472067764235
iterations: 41900 training error: 0.1179898513312659
iterations: 42000 training error: 0.11796501087446858
iterations: 42100 training error: 0.11794019864389872
iterations: 42200 training error: 0.1179154139749157
iterations: 42300 training error: 0.11789065620126928
iterations: 42400 training error: 0.11786592465480568
iterations: 42500 training error: 0.11784121866519454
iterations: 42600 training error: 0.11781653755968217
iterations: 42700 training error: 0.11779188066286798
iterations: 42800 training error: 0.11776724729650892
iterations: 42900 training error: 0.11774263677935072
iterations: 43000 training error: 0.11771804842698808
iterations: 43100 training error: 0.11769348155175473
iterations: 43200 training error: 0.11766893546264533
iterations: 43300 training error: 0.11764440946527004
iterations: 43400 training error: 0.11761990286184622
iterations: 43500 training error: 0.1175954149512234
iterations: 43600 training error: 0.11757094502894977
iterations: 43700 training error: 0.11754649238737751
iterations: 43800 training error: 0.11752205631581249
iterations: 43900 training error: 0.11749763610070503
iterations: 44000 training error: 0.11747323102589236
iterations: 44100 training error: 0.11744884037288439
iterations: 44200 training error: 0.11742446342120334
iterations: 44300 training error: 0.11740009944877551
iterations: 44400 training error: 0.11737574773237712
iterations: 44500 training error: 0.11735140754813438
iterations: 44600 training error: 0.11732707817208525
iterations: 44700 training error: 0.11730275888079722
iterations: 44800 training error: 0.11727844895204594
iterations: 44900 training error: 0.11725414766555581
iterations: 45000 training error: 0.1172298543038011
iterations: 45100 training error: 0.11720556815287003
iterations: 45200 training error: 0.1171812885033892
iterations: 45300 training error: 0.11715701465150999
iterations: 45400 training error: 0.11713274589995361
iterations: 45500 training error: 0.11710848155911419
iterations: 45600 training error: 0.1170842209482179
iterations: 45700 training error: 0.11705996339653404
iterations: 45800 training error: 0.11703570824463312
iterations: 45900 training error: 0.11701145484569271
iterations: 46000 training error: 0.1169872025668394
iterations: 46100 training error: 0.11696295079052493
iterations: 46200 training error: 0.11693869891593019
iterations: 46300 training error: 0.11691444636038847
iterations: 46400 training error: 0.11689019256081958
iterations: 46500 training error: 0.11686593697516894
iterations: 46600 training error: 0.11684167908384117
iterations: 46700 training error: 0.1168174183911183
iterations: 46800 training error: 0.11679315442655455
iterations: 46900 training error: 0.11676888674633575
iterations: 47000 training error: 0.11674461493459559
iterations: 47100 training error: 0.11672033860467737
iterations: 47200 training error: 0.11669605740032989
iterations: 47300 training error: 0.1166717709968325
iterations: 47400 training error: 0.11664747910203399
iterations: 47500 training error: 0.11662318145730198
iterations: 47600 training error: 0.11659887783837268
iterations: 47700 training error: 0.11657456805609344
iterations: 47800 training error: 0.11655025195705329
iterations: 47900 training error: 0.11652592942409648
iterations: 48000 training error: 0.11650160037671455
iterations: 48100 training error: 0.11647726477131383
iterations: 48200 training error: 0.11645292260135898
iterations: 48300 training error: 0.11642857389739159
iterations: 48400 training error: 0.1164042187269209
iterations: 48500 training error: 0.11637985719419912
iterations: 48600 training error: 0.11635548943987155
iterations: 48700 training error: 0.11633111564051758
iterations: 48800 training error: 0.11630673600807975
iterations: 48900 training error: 0.11628235078919233
iterations: 49000 training error: 0.1162579602644124
iterations: 49100 training error: 0.1162335647473625
iterations: 49200 training error: 0.1162091645837932
iterations: 49300 training error: 0.11618476015057135
iterations: 49400 training error: 0.11616035185460154
iterations: 49500 training error: 0.1161359401316906
iterations: 49600 training error: 0.11611152544536206
iterations: 49700 training error: 0.11608710828562446
iterations: 49800 training error: 0.11606268916770497
iterations: 49900 training error: 0.11603826863074967
iterations: 50000 training error: 0.11601384723650117
iterations: 50100 training error: 0.11598942556795397
iterations: 50200 training error: 0.11596500422799386
iterations: 50300 training error: 0.11594058383802805
iterations: 50400 training error: 0.11591616503660288
iterations: 50500 training error: 0.11589174847802138
iterations: 50600 training error: 0.11586733483095439
iterations: 50700 training error: 0.11584292477705337
iterations: 50800 training error: 0.11581851900956498
iterations: 50900 training error: 0.11579411823195099
iterations: 51000 training error: 0.1157697231565123
iterations: 51100 training error: 0.1157453345030218
iterations: 51200 training error: 0.11572095299736845
iterations: 51300 training error: 0.11569657937021176
iterations: 51400 training error: 0.11567221435565142
iterations: 51500 training error: 0.11564785868991212
iterations: 51600 training error: 0.11562351311005051
iterations: 51700 training error: 0.11559917835267974
iterations: 51800 training error: 0.11557485515272103
iterations: 51900 training error: 0.1155505442421826
iterations: 52000 training error: 0.11552624634896774
iterations: 52100 training error: 0.11550196219571676
iterations: 52200 training error: 0.11547769249868715
iterations: 52300 training error: 0.11545343796666996
iterations: 52400 training error: 0.1154291992999522
iterations: 52500 training error: 0.11540497718932133
iterations: 52600 training error: 0.11538077231512099
iterations: 52700 training error: 0.11535658534635443
iterations: 52800 training error: 0.11533241693984352
iterations: 52900 training error: 0.11530826773943757
iterations: 53000 training error: 0.1152841383752846
iterations: 53100 training error: 0.1152600294631546
iterations: 53200 training error: 0.11523594160382473
iterations: 53300 training error: 0.11521187538252235
iterations: 53400 training error: 0.1151878313684278
iterations: 53500 training error: 0.11516381011423671
iterations: 53600 training error: 0.11513981215578227
iterations: 53700 training error: 0.11511583801171599
iterations: 53800 training error: 0.11509188818324632
iterations: 53900 training error: 0.11506796315393518
iterations: 54000 training error: 0.11504406338955016
iterations: 54100 training error: 0.11502018933797092
iterations: 54200 training error: 0.11499634142914913
iterations: 54300 training error: 0.11497252007511968
iterations: 54400 training error: 0.11494872567006068
iterations: 54500 training error: 0.11492495859040194
iterations: 54600 training error: 0.1149012191949786
iterations: 54700 training error: 0.11487750782522688
iterations: 54800 training error: 0.11485382480542451
iterations: 54900 training error: 0.1148301704429652
iterations: 55000 training error: 0.11480654502867493
iterations: 55100 training error: 0.11478294883715941
iterations: 55200 training error: 0.11475938212718562
iterations: 55300 training error: 0.11473584514209324
iterations: 55400 training error: 0.11471233811023326
iterations: 55500 training error: 0.11468886124543443
iterations: 55600 training error: 0.11466541474749065
iterations: 55700 training error: 0.11464199880267319
iterations: 55800 training error: 0.11461861358425979
iterations: 55900 training error: 0.11459525925308302
iterations: 56000 training error: 0.1145719359580943
iterations: 56100 training error: 0.11454864383694086
iterations: 56200 training error: 0.11452538301655549
iterations: 56300 training error: 0.11450215361375538
iterations: 56400 training error: 0.11447895573585146
iterations: 56500 training error: 0.11445578948126127
iterations: 56600 training error: 0.11443265494012933
iterations: 56700 training error: 0.11440955219494874
iterations: 56800 training error: 0.11438648132118542
iterations: 56900 training error: 0.11436344238790128
iterations: 57000 training error: 0.11434043545837498
iterations: 57100 training error: 0.11431746059071905
iterations: 57200 training error: 0.11429451783849057
iterations: 57300 training error: 0.11427160725129465
iterations: 57400 training error: 0.11424872887537776
iterations: 57500 training error: 0.11422588275420542
iterations: 57600 training error: 0.11420306892903252
iterations: 57700 training error: 0.11418028743944887
iterations: 57800 training error: 0.11415753832390932
iterations: 57900 training error: 0.11413482162023982
iterations: 58000 training error: 0.11411213736611753
iterations: 58100 training error: 0.11408948559952203
iterations: 58200 training error: 0.11406686635915277
iterations: 58300 training error: 0.11404427968481108
iterations: 58400 training error: 0.11402172561774043
iterations: 58500 training error: 0.11399920420091979
iterations: 58600 training error: 0.11397671547930989
iterations: 58700 training error: 0.11395425950004094
iterations: 58800 training error: 0.11393183631254156
iterations: 58900 training error: 0.11390944596859964
iterations: 59000 training error: 0.11388708852235334
iterations: 59100 training error: 0.11386476403020096
iterations: 59200 training error: 0.11384247255062839
iterations: 59300 training error: 0.11382021414394398
iterations: 59400 training error: 0.11379798887191692
iterations: 59500 training error: 0.11377579679731267
iterations: 59600 training error: 0.1137536379833168
iterations: 59700 training error: 0.11373151249284619
iterations: 59800 training error: 0.1137094203877363
iterations: 59900 training error: 0.11368736172780577
iterations: 60000 training error: 0.11366533656978968
iterations: 60100 training error: 0.1136433449661413
iterations: 60200 training error: 0.1136213869636996
iterations: 60300 training error: 0.11359946260222209
iterations: 60400 training error: 0.11357757191278464
iterations: 60500 training error: 0.11355571491604895
iterations: 60600 training error: 0.11353389162040822
iterations: 60700 training error: 0.11351210202001205
iterations: 60800 training error: 0.11349034609268262
iterations: 60900 training error: 0.11346862379773755
iterations: 61000 training error: 0.11344693507372937
iterations: 61100 training error: 0.11342527983612212
iterations: 61200 training error: 0.11340365797492619
iterations: 61300 training error: 0.11338206935231249
iterations: 61400 training error: 0.11336051380023544
iterations: 61500 training error: 0.11333899111808757
iterations: 61600 training error: 0.11331750107042404
iterations: 61700 training error: 0.11329604338478116
iterations: 61800 training error: 0.11327461774962908
iterations: 61900 training error: 0.11325322381248838
iterations: 62000 training error: 0.11323186117824888
iterations: 62100 training error: 0.11321052940771992
iterations: 62200 training error: 0.11318922801644685
iterations: 62300 training error: 0.11316795647382398
iterations: 62400 training error: 0.11314671420252881
iterations: 62500 training error: 0.11312550057829847
iterations: 62600 training error: 0.11310431493007284
iterations: 62700 training error: 0.1130831565405066
iterations: 62800 training error: 0.11306202464686416
iterations: 62900 training error: 0.113040918442292
iterations: 63000 training error: 0.11301983707746195
iterations: 63100 training error: 0.11299877966257031
iterations: 63200 training error: 0.11297774526966887
iterations: 63300 training error: 0.11295673293530206
iterations: 63400 training error: 0.1129357416634098
iterations: 63500 training error: 0.1129147704284573
iterations: 63600 training error: 0.1128938181787468
iterations: 63700 training error: 0.1128728838398579
iterations: 63800 training error: 0.11285196631816556
iterations: 63900 training error: 0.11283106450437956
iterations: 64000 training error: 0.11281017727705475
iterations: 64100 training error: 0.11278930350601271
iterations: 64200 training error: 0.11276844205562872
iterations: 64300 training error: 0.11274759178793474
iterations: 64400 training error: 0.11272675156549221
iterations: 64500 training error: 0.11270592025400185
iterations: 64600 training error: 0.11268509672461469
iterations: 64700 training error: 0.11266427985591909
iterations: 64800 training error: 0.11264346853558531
iterations: 64900 training error: 0.11262266166165884
iterations: 65000 training error: 0.11260185814348796
iterations: 65100 training error: 0.11258105690229568
iterations: 65200 training error: 0.11256025687139772
iterations: 65300 training error: 0.11253945699607625
iterations: 65400 training error: 0.11251865623313059
iterations: 65500 training error: 0.11249785355011697
iterations: 65600 training error: 0.11247704792430877
iterations: 65700 training error: 0.11245623834139057
iterations: 65800 training error: 0.11243542379392214
iterations: 65900 training error: 0.11241460327958942
iterations: 66000 training error: 0.1123937757992749
iterations: 66100 training error: 0.11237294035496644
iterations: 66200 training error: 0.11235209594753148
iterations: 66300 training error: 0.11233124157437717
iterations: 66400 training error: 0.11231037622701294
iterations: 66500 training error: 0.11228949888853558
iterations: 66600 training error: 0.112268608531047
iterations: 66700 training error: 0.1122477041130171
iterations: 66800 training error: 0.11222678457659777
iterations: 66900 training error: 0.1122058488448913
iterations: 67000 training error: 0.11218489581917593
iterations: 67100 training error: 0.11216392437608552
iterations: 67200 training error: 0.11214293336473209
iterations: 67300 training error: 0.11212192160377046
iterations: 67400 training error: 0.11210088787838503
iterations: 67500 training error: 0.11207983093718477
iterations: 67600 training error: 0.11205874948898609
iterations: 67700 training error: 0.11203764219945747
iterations: 67800 training error: 0.11201650768760225
iterations: 67900 training error: 0.11199534452204074
iterations: 68000 training error: 0.11197415121705612
iterations: 68100 training error: 0.1119529262283617
iterations: 68200 training error: 0.11193166794853608
iterations: 68300 training error: 0.11191037470207024
iterations: 68400 training error: 0.1118890447399577
iterations: 68500 training error: 0.11186767623375143
iterations: 68600 training error: 0.11184626726899596
iterations: 68700 training error: 0.11182481583793055
iterations: 68800 training error: 0.11180331983133807
iterations: 68900 training error: 0.11178177702939568
iterations: 69000 training error: 0.11176018509135463
iterations: 69100 training error: 0.11173854154384384
iterations: 69200 training error: 0.11171684376755306
iterations: 69300 training error: 0.11169508898200037
iterations: 69400 training error: 0.1116732742280318
iterations: 69500 training error: 0.11165139634761538
iterations: 69600 training error: 0.11162945196041295
iterations: 69700 training error: 0.11160743743647283
iterations: 69800 training error: 0.11158534886425789
iterations: 69900 training error: 0.11156318201301096
iterations: 70000 training error: 0.11154093228823511
iterations: 70100 training error: 0.11151859467873466
iterations: 70200 training error: 0.11149616369327442
iterations: 70300 training error: 0.11147363328438084
iterations: 70400 training error: 0.11145099675613024
iterations: 70500 training error: 0.1114282466518757
iterations: 70600 training error: 0.11140537461669249
iterations: 70700 training error: 0.11138237122776734
iterations: 70800 training error: 0.11135922578391372
iterations: 70900 training error: 0.11133592604268557
iterations: 71000 training error: 0.11131245788997775
iterations: 71100 training error: 0.11128880492231141
iterations: 71200 training error: 0.11126494791591557
iterations: 71300 training error: 0.11124086414903203
iterations: 71400 training error: 0.11121652653459291
iterations: 71500 training error: 0.11119190251028549
iterations: 71600 training error: 0.11116695262438261
iterations: 71700 training error: 0.11114162875483045
iterations: 71800 training error: 0.11111587192054119
iterations: 71900 training error: 0.11108960971982143
iterations: 72000 training error: 0.11106275362870573
iterations: 72100 training error: 0.11103519684420016
iterations: 72200 training error: 0.11100681430012552
iterations: 72300 training error: 0.11097746825665578
iterations: 72400 training error: 0.11094702568783436
iterations: 72500 training error: 0.11091539669462383
iterations: 72600 training error: 0.11088260193845521
iterations: 72700 training error: 0.110848860988277
iterations: 72800 training error: 0.11081465298262684
iterations: 72900 training error: 0.11078066164964917
iterations: 73000 training error: 0.11074756207959412
iterations: 73100 training error: 0.11071576265264729
iterations: 73200 training error: 0.11068529899171389
iterations: 73300 training error: 0.11065593479529848
iterations: 73400 training error: 0.11062734386295599
iterations: 73500 training error: 0.11059924163067077
iterations: 73600 training error: 0.11057143285033555
iterations: 73700 training error: 0.11054380557574867
iterations: 73800 training error: 0.11051630710663249
iterations: 73900 training error: 0.11048892117269317
iterations: 74000 training error: 0.11046165194054587
iterations: 74100 training error: 0.11043451418090365
iterations: 74200 training error: 0.11040752744812292
iterations: 74300 training error: 0.11038071250689024
iterations: 74400 training error: 0.11035408897860575
iterations: 74500 training error: 0.11032767374429438
iterations: 74600 training error: 0.11030147994732717
iterations: 74700 training error: 0.11027551654823757
iterations: 74800 training error: 0.11024978838072347
iterations: 74900 training error: 0.11022429661375008
iterations: 75000 training error: 0.11019903948605773
iterations: 75100 training error: 0.11017401316769321
iterations: 75200 training error: 0.11014921261982567
iterations: 75300 training error: 0.1101246323589641
iterations: 75400 training error: 0.11010026707171776
iterations: 75500 training error: 0.11007611206122656
iterations: 75600 training error: 0.11005216353104394
iterations: 75700 training error: 0.11002841872575553
iterations: 75800 training error: 0.11000487595174371
iterations: 75900 training error: 0.10998153449896111
iterations: 76000 training error: 0.10995839447785483
iterations: 76100 training error: 0.10993545657645104
iterations: 76200 training error: 0.10991272173209551
iterations: 76300 training error: 0.10989019070088765
iterations: 76400 training error: 0.10986786349572739
iterations: 76500 training error: 0.10984573865160217
iterations: 76600 training error: 0.10982381226591167
iterations: 76700 training error: 0.10980207675602358
iterations: 76800 training error: 0.1097805192837539
iterations: 76900 training error: 0.10975911983119632
iterations: 77000 training error: 0.10973784899607075
iterations: 77100 training error: 0.10971666573366415
iterations: 77200 training error: 0.10969551552034786
iterations: 77300 training error: 0.10967432971180566
iterations: 77400 training error: 0.1096530270640187
iterations: 77500 training error: 0.10963151817689468
iterations: 77600 training error: 0.10960971268879037
iterations: 77700 training error: 0.10958752742902719
iterations: 77800 training error: 0.10956489219273914
iterations: 77900 training error: 0.10954174956027961
iterations: 78000 training error: 0.1095180467423844
iterations: 78100 training error: 0.10949371966247669
iterations: 78200 training error: 0.10946867040321075
iterations: 78300 training error: 0.10944273764386424
iterations: 78400 training error: 0.10941565615948569
iterations: 78500 training error: 0.109386996730347
iterations: 78600 training error: 0.10935607265245557
iterations: 78700 training error: 0.10932179528114377
iterations: 78800 training error: 0.10928246597769982
iterations: 78900 training error: 0.10923552690549278
iterations: 79000 training error: 0.10917740312439722
iterations: 79100 training error: 0.10910379887145709
iterations: 79200 training error: 0.10901104452523908
iterations: 79300 training error: 0.10889865613304098
iterations: 79400 training error: 0.10877129095623114
iterations: 79500 training error: 0.10863696806914018
iterations: 79600 training error: 0.10850246265193396
iterations: 79700 training error: 0.10837084638126347
iterations: 79800 training error: 0.1082424150762343
iterations: 79900 training error: 0.10811640526683833
iterations: 80000 training error: 0.10799196317716907
iterations: 80100 training error: 0.10786844502713469
iterations: 80200 training error: 0.10774543392114498
iterations: 80300 training error: 0.1076226836466158
iterations: 80400 training error: 0.10750006099611044
iterations: 80500 training error: 0.1073775027525916
iterations: 80600 training error: 0.1072549873019064
iterations: 80700 training error: 0.10713251755732278
iterations: 80800 training error: 0.10701011195231182
iterations: 80900 training error: 0.10688780091449943
iterations: 81000 training error: 0.10676562681112796
iterations: 81100 training error: 0.1066436457636619
iterations: 81200 training error: 0.10652193001952145
iterations: 81300 training error: 0.10640056981990373
iterations: 81400 training error: 0.10627967397517532
iterations: 81500 training error: 0.10615936867947977
iterations: 81600 training error: 0.1060397944500627
iterations: 81700 training error: 0.10592110141907313
iterations: 81800 training error: 0.10580344347918427
iterations: 81900 training error: 0.1056869719436496
iterations: 82000 training error: 0.10557182940956136
iterations: 82100 training error: 0.10545814442590688
iterations: 82200 training error: 0.10534602740461828
iterations: 82300 training error: 0.10523556801908489
iterations: 82400 training error: 0.10512683414858744
iterations: 82500 training error: 0.10501987227173316
iterations: 82600 training error: 0.10491470909589781
iterations: 82700 training error: 0.1048113541329228
iterations: 82800 training error: 0.10470980289071748
iterations: 82900 training error: 0.10461004034283782
iterations: 83000 training error: 0.10451204436054196
iterations: 83100 training error: 0.10441578883997611
iterations: 83200 training error: 0.10432124632444996
iterations: 83300 training error: 0.10422838999929857
iterations: 83400 training error: 0.1041371950147052
iterations: 83500 training error: 0.10404763916102032
iterations: 83600 training error: 0.10395970297496232
iterations: 83700 training error: 0.10387336939032707
iterations: 83800 training error: 0.10378862306342611
iterations: 83900 training error: 0.1037054495038682
iterations: 84000 training error: 0.1036238341294431
iterations: 84100 training error: 0.10354376134415022
iterations: 84200 training error: 0.10346521371488596
iterations: 84300 training error: 0.10338817129826348
iterations: 84400 training error: 0.10331261114682586
iterations: 84500 training error: 0.10323850700494197
iterations: 84600 training error: 0.10316582918959315
iterations: 84700 training error: 0.10309454464019416
iterations: 84800 training error: 0.10302461711423465
iterations: 84900 training error: 0.10295600750139342
iterations: 85000 training error: 0.10288867422727965
iterations: 85100 training error: 0.10282257371848276
iterations: 85200 training error: 0.10275766090261262
iterations: 85300 training error: 0.10269388971997938
iterations: 85400 training error: 0.10263121362707905
iterations: 85500 training error: 0.10256958607581837
iterations: 85600 training error: 0.1025089609561054
iterations: 85700 training error: 0.10244929299297101
iterations: 85800 training error: 0.10239053809253336
iterations: 85900 training error: 0.10233265363389409
iterations: 86000 training error: 0.1022755987063738
iterations: 86100 training error: 0.10221933429337517
iterations: 86200 training error: 0.10216382340561804
iterations: 86300 training error: 0.10210903116755397
iterations: 86400 training error: 0.10205492486150639
iterations: 86500 training error: 0.10200147393449951
iterations: 86600 training error: 0.10194864997292469
iterations: 86700 training error: 0.10189642665019748
iterations: 86800 training error: 0.10184477965236689
iterations: 86900 training error: 0.10179368658637472
iterations: 87000 training error: 0.10174312687529183
iterations: 87100 training error: 0.1016930816444456
iterations: 87200 training error: 0.10164353360190946
iterations: 87300 training error: 0.10159446691636853
iterations: 87400 training error: 0.10154586709493124
iterations: 87500 training error: 0.10149772086303466
iterations: 87600 training error: 0.10145001604816323
iterations: 87700 training error: 0.10140274146876121
iterations: 87800 training error: 0.10135588682935047
iterations: 87900 training error: 0.10130944262258396
iterations: 88000 training error: 0.10126340003869225
iterations: 88100 training error: 0.10121775088256152
iterations: 88200 training error: 0.10117248749847968
iterations: 88300 training error: 0.10112760270244343
iterations: 88400 training error: 0.1010830897217805
iterations: 88500 training error: 0.10103894214175024
iterations: 88600 training error: 0.10099515385871455
iterations: 88700 training error: 0.10095171903940765
iterations: 88800 training error: 0.10090863208582088
iterations: 88900 training error: 0.10086588760518479
iterations: 89000 training error: 0.10082348038454758
iterations: 89100 training error: 0.10078140536943449
iterations: 89200 training error: 0.10073965764612398
iterations: 89300 training error: 0.10069823242706537
iterations: 89400 training error: 0.1006571250390215
iterations: 89500 training error: 0.10061633091353492
iterations: 89600 training error: 0.1005758455793643
iterations: 89700 training error: 0.10053566465655576
iterations: 89800 training error: 0.10049578385186915
iterations: 89900 training error: 0.1004561989553051
iterations: 90000 training error: 0.10041690583749474
iterations: 90100 training error: 0.10037790044778189
iterations: 90200 training error: 0.10033917881281847
iterations: 90300 training error: 0.10030073703553893
iterations: 90400 training error: 0.10026257129440601
iterations: 90500 training error: 0.10022467784282206
iterations: 90600 training error: 0.10018705300864561
iterations: 90700 training error: 0.10014969319373894
iterations: 90800 training error: 0.10011259487351326
iterations: 90900 training error: 0.10007575459643117
iterations: 91000 training error: 0.10003916898344399
iterations: 91100 training error: 0.10000283472734511
iterations: 91200 training error: 0.09996674859204062
iterations: 91300 training error: 0.09993090741171337
iterations: 91400 training error: 0.09989530808990561
iterations: 91500 training error: 0.09985994759849778
iterations: 91600 training error: 0.09982482297660726
iterations: 91700 training error: 0.09978993132940675
iterations: 91800 training error: 0.09975526982686903
iterations: 91900 training error: 0.09972083570244991
iterations: 92000 training error: 0.09968662625171718
iterations: 92100 training error: 0.09965263883093288
iterations: 92200 training error: 0.09961887085559899
iterations: 92300 training error: 0.09958531979897463
iterations: 92400 training error: 0.09955198319057056
iterations: 92500 training error: 0.09951885861463279
iterations: 92600 training error: 0.09948594370861161
iterations: 92700 training error: 0.09945323616163795
iterations: 92800 training error: 0.09942073371299635
iterations: 92900 training error: 0.09938843415060981
iterations: 93000 training error: 0.0993563353095353
iterations: 93100 training error: 0.09932443507047817
iterations: 93200 training error: 0.09929273135832146
iterations: 93300 training error: 0.09926122214068447
iterations: 93400 training error: 0.09922990542650365
iterations: 93500 training error: 0.09919877926463679
iterations: 93600 training error: 0.09916784174250444
iterations: 93700 training error: 0.09913709098475469
iterations: 93800 training error: 0.09910652515196523
iterations: 93900 training error: 0.09907614243937846
iterations: 94000 training error: 0.09904594107566626
iterations: 94100 training error: 0.09901591932173673
iterations: 94200 training error: 0.09898607546957003
iterations: 94300 training error: 0.0989564078410973
iterations: 94400 training error: 0.09892691478710965
iterations: 94500 training error: 0.09889759468620764
iterations: 94600 training error: 0.09886844594378537
iterations: 94700 training error: 0.09883946699105585
iterations: 94800 training error: 0.09881065628410468
iterations: 94900 training error: 0.09878201230298932
iterations: 95000 training error: 0.0987535335508676
iterations: 95100 training error: 0.09872521855316421
iterations: 95200 training error: 0.09869706585677611
iterations: 95300 training error: 0.09866907402930498
iterations: 95400 training error: 0.0986412416583301
iterations: 95500 training error: 0.09861356735071328
iterations: 95600 training error: 0.0985860497319337
iterations: 95700 training error: 0.09855868744545714
iterations: 95800 training error: 0.0985314791521378
iterations: 95900 training error: 0.09850442352964875
iterations: 96000 training error: 0.09847751927193638
iterations: 96100 training error: 0.09845076508871445
iterations: 96200 training error: 0.09842415970497705
iterations: 96300 training error: 0.09839770186054038
iterations: 96400 training error: 0.09837139030961117
iterations: 96500 training error: 0.09834522382037876
iterations: 96600 training error: 0.09831920117463015
iterations: 96700 training error: 0.09829332116738737
iterations: 96800 training error: 0.09826758260656929
iterations: 96900 training error: 0.09824198431267057
iterations: 97000 training error: 0.09821652511845981
iterations: 97100 training error: 0.09819120386869823
iterations: 97200 training error: 0.09816601941987584
iterations: 97300 training error: 0.09814097063996262
iterations: 97400 training error: 0.09811605640817515
iterations: 97500 training error: 0.09809127561475972
iterations: 97600 training error: 0.09806662716078568
iterations: 97700 training error: 0.09804210995795683
iterations: 97800 training error: 0.09801772292842814
iterations: 97900 training error: 0.0979934650046411
iterations: 98000 training error: 0.09796933512916238
iterations: 98100 training error: 0.09794533225453524
iterations: 98200 training error: 0.09792145534313888
iterations: 98300 training error: 0.09789770336706205
iterations: 98400 training error: 0.09787407530796925
iterations: 98500 training error: 0.09785057015699196
iterations: 98600 training error: 0.09782718691461104
iterations: 98700 training error: 0.09780392459055434
iterations: 98800 training error: 0.09778078220369417
iterations: 98900 training error: 0.09775775878195074
iterations: 99000 training error: 0.09773485336220315
iterations: 99100 training error: 0.09771206499019741
iterations: 99200 training error: 0.09768939272046268
iterations: 99300 training error: 0.09766683561623059
iterations: 99400 training error: 0.09764439274935317
iterations: 99500 training error: 0.09762206320022568
iterations: 99600 training error: 0.09759984605771255
iterations: 99700 training error: 0.0975777404190737
iterations: 99800 training error: 0.09755574538988954
iterations: 99900 training error: 0.09753386008399151
{ error: 0.09751230085207528, iterations: 100000 }
train time: 341934ms
[ { url: 'http://www.rajaut.cz/85495-audi-a6-allroad-30-tdi',
    mark: 0.5,
    evaluatedMark: 0.757601256405481 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/a8/14825288',
    mark: 0.25,
    evaluatedMark: 0.14117912723165266 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/a8/15017895',
    mark: 1,
    evaluatedMark: 0.5465033214503401 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/rada-3/14997196',
    mark: 0.25,
    evaluatedMark: 0.44237825525743624 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/rada-5/15178599',
    mark: 0.5,
    evaluatedMark: 0.3445725866436017 },
  { url: 'http://www.cars.cz/inzerce/osobni-auto-O/BMW/X3/X3-2.5-i-Hatchback-13949048234541652.html?clksrc=Y2Fyc2hwX2NsaWNrWzhd',
    mark: 0.25,
    evaluatedMark: 0.05656172219272046 },
  { url: 'http://www.sauto.cz/osobni/detail/skoda/superb/15336144',
    mark: 0,
    evaluatedMark: 0.000002069652623959149 },
  { url: 'http://www.sauto.cz/osobni/detail/skoda/fabia/14503063',
    mark: 1,
    evaluatedMark: 0.8096634881958102 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/a7/15246806',
    mark: 0.5,
    evaluatedMark: 0.32713981924419977 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/a6/15358416',
    mark: 0,
    evaluatedMark: 0.21014731239712034 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/m3/12704780',
    mark: 1,
    evaluatedMark: 0.8100627332836194 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/q3/15189278',
    mark: 1,
    evaluatedMark: 0.9399156208347974 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/rada-5/14998149',
    mark: 0.5,
    evaluatedMark: 0.3032426092226069 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/q7/15177961',
    mark: 0,
    evaluatedMark: 0.7200336156528439 },
  { url: 'http://www.dasweltauto.cz/cs/Car/712920/q7-3-0-tdi-quattro-tiptronic',
    mark: 1,
    evaluatedMark: 0.7452664486608978 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/rada-3/10551345',
    mark: 0,
    evaluatedMark: 0.17700018936860054 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/a4/15097347',
    mark: 0,
    evaluatedMark: 0.1359399753427607 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/a4/15057186',
    mark: 0.5,
    evaluatedMark: 0.08540542820726395 },
  { url: 'http://osobni.auto-iq.cz/bmw_bmw_rada_3_320d-xdrive-sedan-inz350611.html?search=1&category=1&buy=0&',
    mark: 0.5,
    evaluatedMark: 0.24024177302658747 },
  { url: 'http://osobni.auto-iq.cz/bmw_bmw_rada_5_530d-xdrive-sedan-inz334997.html?search=1&category=1&buy=0&',
    mark: 0.5,
    evaluatedMark: 0.3353385306207524 },
  { url: 'http://osobni.auto-iq.cz/bmw_rada-3gt_320d-xdrive-gt-inz335035.html?search=1&category=1&buy=0&',
    mark: 0,
    evaluatedMark: 0.15369611912807968 },
  { url: 'http://osobni.auto-iq.cz/bmw_bmw_rada_5_520d-xdrive-touring-inz365451.html?search=1&category=1&buy=0&',
    mark: 0.5,
    evaluatedMark: 0.16197218954786574 },
  { url: 'http://osobni.auto-iq.cz/skoda_skoda_superb_com-ii-2-0-tdi-cr-4x4-125-kw-inz343259.html?search=1&category=1&buy=0&',
    mark: 0,
    evaluatedMark: 0.0008143469227912684 },
  { url: 'http://osobni.auto-iq.cz/bmw_bmw_x6_x6-m50d-inz365416.html?search=1&category=1&buy=0&',
    mark: 1,
    evaluatedMark: 0.6871264964758346 },
  { url: 'http://osobni.auto-iq.cz/bmw_bmw_rada_5_530d-xdrive-sedan-inz365428.html?search=1&category=1&buy=0&',
    mark: 0.75,
    evaluatedMark: 0.3662898970430997 },
  { url: 'http://osobni.auto-iq.cz/bmw_bmw_rada_6_640d-xdrive-gran-coupe-inz365425.html?search=1&category=1&buy=0&',
    mark: 0.5,
    evaluatedMark: 0.14570281200134638 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/q3/14959766',
    mark: 0,
    evaluatedMark: 0.12179468598690192 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/q5/15178244',
    mark: 1,
    evaluatedMark: 0.7665207992166907 },
  { url: 'http://osobni.auto-iq.cz/skoda_skoda_superb_com-ii-fl-2-0-tdi-cr-dsg-125-k-inz366782.html?search=1&category=1&buy=0&',
    mark: 0,
    evaluatedMark: 0.0009904320253445757 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/x5/14483845',
    mark: 0,
    evaluatedMark: 0.1811176431697192 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/rada-3/12526716',
    mark: 0,
    evaluatedMark: 0.0021169082225852495 },
  { url: 'http://osobni.auto-iq.cz/bmw_bmw_x5_x5-xdrive-30d-inz365442.html?search=1&category=1&buy=0&',
    mark: 0,
    evaluatedMark: 0.2877468011900572 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/rada-4/15178586',
    mark: 0.5,
    evaluatedMark: 0.47185661148118113 },
  { url: 'http://osobni.auto-iq.cz/bmw_bmw_rada_5_530d-xdrive-touring-steptr-xe-inz356395.html?search=1&category=1&buy=0&',
    mark: 1,
    evaluatedMark: 0.9989302638899413 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/a6/14966715',
    mark: 0.75,
    evaluatedMark: 0.6088682378524497 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/a6/14906795',
    mark: 1,
    evaluatedMark: 0.5321344662942191 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/a8/15017888',
    mark: 1,
    evaluatedMark: 0.5351423090166557 },
  { url: 'http://www.annonce.cz/inzerat/audi-tt-rs-coupe-2-5-24757814-wmpxgj.html',
    mark: 0.5,
    evaluatedMark: 0.2405080923247362 },
  { url: 'http://www.sauto.cz/osobni/detail/audi/ostatni/15165600',
    mark: 0.25,
    evaluatedMark: 0.10899661184616032 },
  { url: 'http://osobni.auto-iq.cz/bmw_bmw_rada_3_320d-xdrive-sedan-inz361757.html?search=1&category=1&buy=0&',
    mark: 0,
    evaluatedMark: 0.262096082367286 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/rada-3/14657128',
    mark: 0,
    evaluatedMark: 0.19345219176980352 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/rada-5/15004229',
    mark: 0.5,
    evaluatedMark: 0.5411608807907655 },
  { url: 'http://www.dobrakoupe.cz/bmw/bmw_rada_5_30_m550d_adaptivedrive_tv_1386478.htm',
    mark: 0,
    evaluatedMark: 9.865393643947923e-32 },
  { url: 'http://www.sauto.cz/osobni/detail/bmw/rada-5/14992719',
    mark: 0.25,
    evaluatedMark: 0.462741185213404 } ]
Avarage error: 0.2066292717058766
