% Python_3.6.0.
% Sklearn_0.18.1.
% NumPy_1.13.0.
% SciPy_0.19.1.
% Sun Jul 16 17:19:21 2017
% Created by run_task()
@RELATION openml_task_9985_predictions

@ATTRIBUTE repeat NUMERIC
@ATTRIBUTE fold NUMERIC
@ATTRIBUTE sample NUMERIC
@ATTRIBUTE row_id NUMERIC
@ATTRIBUTE confidence.1 NUMERIC
@ATTRIBUTE confidence.2 NUMERIC
@ATTRIBUTE confidence.3 NUMERIC
@ATTRIBUTE confidence.4 NUMERIC
@ATTRIBUTE confidence.5 NUMERIC
@ATTRIBUTE confidence.6 NUMERIC
@ATTRIBUTE prediction {1, 2, 3, 4, 5, 6}
@ATTRIBUTE correct {1, 2, 3, 4, 5, 6}

@DATA
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0,9,0,5248,0.166659580221,0.168108521073,0.166629965368,0.165717665292,0.166183630609,0.166700637436,2,2
0,9,0,4902,0.167840056052,0.167687367406,0.167447927762,0.167913547768,0.165571864025,0.163539236988,1,2
0,9,0,3670,0.167257030845,0.167494560116,0.166288402116,0.166358415682,0.166333047887,0.166268543353,2,2
0,9,0,4827,0.167190057248,0.167092871422,0.167722642673,0.166258780104,0.16514101483,0.166594633723,3,2
0,9,0,934,0.168149858216,0.168064973169,0.166699672784,0.16610068785,0.164691026016,0.166293781965,2,2
0,9,0,4096,0.167209080566,0.166379269278,0.166288243394,0.166407547207,0.165770019294,0.167945840261,6,2
0,9,0,2543,0.166795261003,0.166088558416,0.167718259282,0.16595830157,0.167252969919,0.16618664981,3,2
0,9,0,1668,0.167303199436,0.167165236849,0.166057437008,0.166735395332,0.165963765551,0.166774965824,1,2
0,9,0,3212,0.167258662467,0.166120444031,0.165931988905,0.167151955321,0.166358359428,0.167178589849,1,2
0,9,0,1095,0.167686198148,0.166125194356,0.166020742259,0.167533869996,0.165477470152,0.167156525088,1,2
0,9,0,120,0.166999388567,0.166697697615,0.166712722967,0.16625431841,0.166365542943,0.166970329498,6,2
0,9,0,644,0.166459589994,0.167109315005,0.16758869407,0.16570237313,0.166389865771,0.166750162029,2,2
0,9,0,224,0.167273461835,0.167264651702,0.166954320127,0.165986195531,0.165048879353,0.167472491453,6,2
0,9,0,3509,0.165717979913,0.167309458331,0.167419376119,0.165839819871,0.166312723158,0.167400642608,6,2
0,9,0,4831,0.166981013399,0.166407463277,0.166797564317,0.166578618658,0.166383329741,0.166852010609,1,2
0,9,0,5186,0.166976755175,0.166810711981,0.167505532987,0.165682244923,0.166289982417,0.166734772517,3,2
0,9,0,5518,0.167373238902,0.167517700124,0.167628449205,0.165959140367,0.166869485656,0.164651985745,3,2
0,9,0,3784,0.168686980484,0.165792394813,0.165185480028,0.168048546816,0.165586323969,0.16670027389,1,2
0,9,0,5023,0.167305857126,0.166630040171,0.166178033672,0.165896443979,0.165661193349,0.168328431703,6,2
0,9,0,4317,0.166842127684,0.167638117223,0.167119036738,0.167102594609,0.165196819567,0.166101304179,2,2
0,9,0,1268,0.167748240132,0.166826285622,0.165794746215,0.167065290489,0.166127055948,0.166438381593,1,2
0,9,0,5257,0.167845657933,0.168700653412,0.166563202046,0.165895021973,0.164719203691,0.166276260945,2,2
0,9,0,5775,0.166800161456,0.168036503892,0.166083279349,0.166431166198,0.165956753975,0.16669213513,2,2
0,9,0,3976,0.167133843057,0.166548064867,0.16698796444,0.166501490157,0.166882202452,0.165946435026,1,2
0,9,0,674,0.167065169467,0.167558806206,0.16690746112,0.166427295001,0.165222712491,0.166818555714,2,2
0,9,0,5339,0.166972198846,0.167933450711,0.165778478693,0.16715626951,0.165652991867,0.166506610372,2,2
0,9,0,1756,0.167063806008,0.166865887107,0.16591680449,0.167742299223,0.165125773108,0.167285430063,4,2
0,9,0,3069,0.16690119447,0.165705163121,0.166400937576,0.167085550311,0.167004893368,0.166902261155,1,2
0,9,0,4123,0.166744899481,0.167613025295,0.167104040785,0.167572087159,0.165077037128,0.165888910152,2,2
0,9,0,802,0.167279827193,0.167698132776,0.167194880971,0.166535880115,0.164967825241,0.166323453703,2,2
0,9,0,3650,0.166721374608,0.167307634162,0.165667279213,0.16791065089,0.165141996704,0.167251064423,4,2
0,9,0,5888,0.166803201845,0.167152414784,0.166033381308,0.165886453685,0.165930972101,0.168193576277,6,2
0,9,0,4701,0.167326899472,0.167409649278,0.166453463754,0.166538431873,0.165211675059,0.167059880564,2,2
0,9,0,4075,0.166838724126,0.166547918025,0.165297909542,0.167268108527,0.165940724809,0.16810661497,6,2
0,9,0,3401,0.166745531443,0.165954927057,0.167157746611,0.166574821756,0.165666974531,0.167899998602,6,2
0,9,0,3803,0.167300823769,0.167317945267,0.165384185036,0.166701625856,0.166034398621,0.16726102145,6,2
0,9,0,2594,0.167132352318,0.166075035588,0.166890028512,0.166402210836,0.167003514985,0.16649685776,1,2
0,9,0,1435,0.167084298555,0.165245391602,0.165955235499,0.167286038963,0.166252705799,0.168176329581,6,2
0,9,0,1682,0.166466714974,0.168372881179,0.165828880953,0.166954957159,0.165043361914,0.167333203821,6,2
0,9,0,5175,0.166666059043,0.167597858372,0.165993888612,0.166622037165,0.166160555182,0.166959601626,6,2
0,9,0,1768,0.166339758193,0.166315332496,0.167669148438,0.167102783603,0.165063836367,0.167509140903,6,2
0,9,0,4953,0.168113275774,0.167893353813,0.167585068206,0.167759212426,0.165294265419,0.163354824361,2,2
0,9,0,5516,0.167018827542,0.166950272528,0.165463463541,0.166795918509,0.166107062026,0.167664455854,6,2
0,9,0,4500,0.168231195222,0.167284905967,0.167525183978,0.167024061253,0.166556772564,0.163377881016,1,2
0,9,0,5956,0.167095754232,0.167281656087,0.16577047142,0.167491117428,0.165836668617,0.166524332216,2,2
0,9,0,5449,0.167718632503,0.168269805184,0.167173679746,0.167328501782,0.165956555252,0.163552825533,2,2
0,9,0,3668,0.166391338974,0.168540707974,0.1657971567,0.166461711132,0.165945845662,0.166863239558,6,2
0,9,0,800,0.167096515081,0.167763204383,0.167198695032,0.166937448152,0.164862911562,0.16614122579,2,2
% 
% 
%