% Python_3.6.0.
% Sklearn_0.18.1.
% NumPy_1.13.0.
% SciPy_0.19.1.
% Sun Jul 16 21:51:29 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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0,9,0,2101,0.183447124983,0.128461381802,0.140717059009,0.182811260358,0.183527756915,0.181035416932,5,1
0,9,0,4797,0.200834728266,0.164065332231,0.131381697231,0.175795505612,0.143579834501,0.184342902159,1,1
0,9,0,5248,0.19090764244,0.1891934764,0.171574964796,0.134079651426,0.135291558362,0.178952706575,1,2
0,9,0,4902,0.181061853403,0.178554492682,0.181002136476,0.179867292058,0.170345730253,0.109168495128,1,2
0,9,0,3670,0.17469131457,0.176739864804,0.15511543054,0.163404874734,0.166479614892,0.163568900461,2,2
0,9,0,4827,0.174226281603,0.169596831283,0.187932801554,0.177019426438,0.123961570781,0.167263088341,3,2
0,9,0,934,0.175661583726,0.213122224064,0.189900632127,0.122495175139,0.0903995885128,0.208420796432,2,2
0,9,0,4096,0.181099667725,0.176130882631,0.165332166448,0.153183214884,0.136689251373,0.187564816938,6,2
0,9,0,2543,0.177506145568,0.168953915293,0.171055389826,0.142135617898,0.187529702643,0.152819228772,5,2
0,9,0,1668,0.183075611436,0.170323880471,0.14975062537,0.161951486883,0.160026890914,0.174871504926,1,2
0,9,0,3212,0.184638987155,0.153890950869,0.155477755781,0.174880612544,0.154571222212,0.176540471439,1,2
0,9,0,1095,0.184429326816,0.163134436023,0.170562959996,0.152829704035,0.143767494112,0.185276079019,6,2
0,9,0,120,0.166277969362,0.171438066671,0.168871514717,0.156070503513,0.158006007119,0.179335938619,6,2
0,9,0,644,0.162072761282,0.180926795808,0.169208829405,0.137229807063,0.172360390605,0.178201415836,2,2
0,9,0,224,0.166926045699,0.169037230356,0.181085016928,0.169408440982,0.130448418376,0.18309484766,6,2
0,9,0,3509,0.142856850168,0.182809790084,0.184851733243,0.14728227427,0.157357375568,0.184841976667,3,2
0,9,0,4831,0.176811311161,0.148892288152,0.171076872633,0.168620158897,0.161870964617,0.172728404539,1,2
0,9,0,5186,0.172248115245,0.177046237387,0.186851932284,0.156771402908,0.125096890843,0.181985421332,3,2
0,9,0,5518,0.188100678488,0.195387632799,0.19342374852,0.160272413007,0.148772638418,0.114042888769,2,2
0,9,0,3784,0.194195838992,0.158483143248,0.148890056132,0.178394231644,0.143993631465,0.176043098518,1,2
0,9,0,5023,0.189488565783,0.174371276517,0.158984489635,0.137451099965,0.14429464378,0.19540992432,6,2
0,9,0,4317,0.176719537832,0.176252617317,0.172102980271,0.167027738985,0.146889140576,0.161007985019,1,2
0,9,0,1268,0.184128431407,0.178850416874,0.151026635953,0.176016542773,0.133009338527,0.176968634466,1,2
0,9,0,5257,0.175338084612,0.212426528859,0.17695871936,0.118304290022,0.10147445883,0.215497918318,6,2
0,9,0,5775,0.167680751125,0.187274231787,0.164897593113,0.148008652067,0.162461278922,0.169677492987,2,2
0,9,0,3976,0.180708030842,0.156349037156,0.178130143334,0.14685109053,0.179475810754,0.158485887384,1,2
0,9,0,674,0.168804685874,0.189376734199,0.192328751862,0.144692701487,0.122261586916,0.182535539661,3,2
0,9,0,5339,0.187889807714,0.176411902473,0.147314864111,0.164099899496,0.152020744346,0.172262781859,1,2
0,9,0,1756,0.174945350485,0.194641059113,0.128340520008,0.187748272288,0.118365160656,0.195959637451,6,2
0,9,0,3069,0.172456109222,0.157103488425,0.168514310402,0.156490504316,0.162960486808,0.182475100827,6,2
0,9,0,4123,0.154164167648,0.197885848098,0.178850075852,0.181342526236,0.124395847412,0.163361534754,2,2
0,9,0,802,0.190607019049,0.183482120801,0.182203739259,0.169241738643,0.124555859633,0.149909522615,1,2
0,9,0,3650,0.178349664117,0.189526223491,0.12141178462,0.188890552153,0.12715229702,0.194669478599,6,2
0,9,0,5888,0.180814614249,0.170257379379,0.157228259784,0.153521581956,0.157135308975,0.181042855657,6,2
0,9,0,4701,0.178080623809,0.180826205261,0.164632838127,0.168884597079,0.134025285469,0.173550450256,2,2
0,9,0,4075,0.182435630319,0.170710596402,0.124852635961,0.19049236152,0.136899952759,0.19460882304,6,2
0,9,0,3401,0.205735441545,0.122952903493,0.222175050093,0.132574598744,0.128321945257,0.188240060867,3,2
0,9,0,3803,0.186637425,0.178447347818,0.141166194692,0.149847596478,0.153568319136,0.190333116876,6,2
0,9,0,2594,0.180309984364,0.151207279763,0.178516264564,0.15040739938,0.172004058602,0.167555013326,1,2
0,9,0,1435,0.181974827255,0.121136780835,0.159968452227,0.18558144088,0.163560141541,0.187778357261,6,2
0,9,0,1682,0.175893388062,0.190154589854,0.127253543133,0.19609984735,0.117847808994,0.192750822607,4,2
0,9,0,5175,0.163363801555,0.167937352823,0.159080482265,0.158919204257,0.165043200687,0.185655958412,6,2
0,9,0,1768,0.169505812275,0.154300331956,0.163928862817,0.175821082318,0.141897737902,0.194546172731,6,2
0,9,0,4953,0.183260353913,0.180937702431,0.177249416059,0.182312120926,0.168795535912,0.107444870759,1,2
0,9,0,5516,0.155356558372,0.182895818751,0.142647733627,0.175024807505,0.153910922986,0.190164158759,6,2
0,9,0,4500,0.188155122916,0.173879206908,0.17323034254,0.172543379528,0.18063424112,0.111557706988,1,2
0,9,0,5956,0.178031726257,0.17691708231,0.142988266033,0.18303257278,0.150478375221,0.1685519774,4,2
0,9,0,5449,0.185328006781,0.185884567369,0.183313346714,0.170757446778,0.160941723055,0.113774909303,2,2
0,9,0,3668,0.162599152833,0.178169465354,0.154967048103,0.14662652952,0.17131214733,0.18632565686,6,2
0,9,0,800,0.17468630223,0.191012051998,0.189575295483,0.171895657826,0.108311195367,0.164519497096,2,2
% 
% 
%