% Python_3.6.0.
% Sklearn_0.18.1.
% NumPy_1.13.0.
% SciPy_0.19.1.
% Mon Jul 17 00:07:13 2017
% Created by run_task()
@RELATION openml_task_3950_predictions

@ATTRIBUTE repeat NUMERIC
@ATTRIBUTE fold NUMERIC
@ATTRIBUTE sample NUMERIC
@ATTRIBUTE row_id NUMERIC
@ATTRIBUTE confidence.0 NUMERIC
@ATTRIBUTE confidence.1 NUMERIC
@ATTRIBUTE prediction {0, 1}
@ATTRIBUTE correct {0, 1}

@DATA
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0,9,0,302,0.017900047672,0.982099952328,1,1
0,9,0,841,0.00568842921784,0.994311570782,1,1
0,9,0,121,0.00333333333333,0.996666666667,1,1
0,9,0,878,0.233898551095,0.766101448905,1,1
0,9,0,174,0.0648977662348,0.935102233765,1,1
0,9,0,18,0.0837240813636,0.916275918636,1,1
0,9,0,11,0.517807569661,0.482192430339,0,1
0,9,0,472,0.758758773662,0.241241226338,0,1
0,9,0,584,0.340779651125,0.659220348875,1,1
0,9,0,576,0.300525066847,0.699474933153,1,1
0,9,0,503,0.0,1.0,1,1
0,9,0,206,0.0363101014575,0.963689898543,1,1
0,9,0,132,0.0234627193196,0.97653728068,1,1
0,9,0,984,0.222050565883,0.777949434117,1,1
0,9,0,909,0.100261513096,0.899738486904,1,1
0,9,0,492,0.242352038131,0.757647961869,1,1
0,9,0,937,0.0337904694686,0.966209530531,1,1
0,9,0,408,0.0,1.0,1,1
0,9,0,892,0.057379084417,0.942620915583,1,1
0,9,0,52,0.0203055555556,0.979694444444,1,1
0,9,0,542,0.416231755339,0.583768244661,1,1
0,9,0,239,0.017900047672,0.982099952328,1,1
0,9,0,816,0.0246600967882,0.975339903212,1,1
0,9,0,82,0.0181313131313,0.981868686869,1,1
0,9,0,232,0.0173684622567,0.982631537743,1,1
0,9,0,516,0.00947619047619,0.990523809524,1,1
0,9,0,554,0.00454545454545,0.995454545455,1,1
0,9,0,448,0.136655429871,0.863344570129,1,1
0,9,0,846,0.00647058823529,0.993529411765,1,1
0,9,0,217,0.0764040974637,0.923595902536,1,1
0,9,0,983,0.207436795194,0.792563204806,1,1
0,9,0,362,0.0,1.0,1,1
0,9,0,356,0.0174106296826,0.982589370317,1,1
0,9,0,85,0.0181313131313,0.981868686869,1,1
0,9,0,22,0.0429065326997,0.9570934673,1,1
0,9,0,190,0.0440605272777,0.955939472722,1,1
0,9,0,92,0.0117362817363,0.988263718264,1,1
0,9,0,941,0.217900565319,0.782099434681,1,1
0,9,0,549,0.0835250105355,0.916474989464,1,1
0,9,0,716,0.0942473700842,0.905752629916,1,1
0,9,0,299,0.00144444444444,0.998555555556,1,1
0,9,0,551,0.0460847975554,0.953915202445,1,1
0,9,0,661,0.175317873132,0.824682126868,1,1
0,9,0,102,0.00726851851852,0.992731481481,1,1
0,9,0,1010,0.202050490159,0.797949509841,1,1
0,9,0,530,0.0802469909254,0.919753009075,1,1
0,9,0,290,0.0,1.0,1,1
0,9,0,208,0.0363101014575,0.963689898543,1,1
0,9,0,988,0.194501738021,0.805498261979,1,1
0,9,0,665,0.0479814337586,0.952018566241,1,1
0,9,0,803,0.00795148315737,0.992048516843,1,1
0,9,0,447,0.524845673884,0.475154326116,0,1
0,9,0,786,0.0320687931245,0.967931206875,1,1
0,9,0,381,0.0,1.0,1,1
0,9,0,181,0.0483920762544,0.951607923746,1,1
0,9,0,34,0.0301387943447,0.969861205655,1,1
0,9,0,735,0.135410262393,0.864589737607,1,1
0,9,0,148,0.00529411764706,0.994705882353,1,1
0,9,0,98,0.0632372885641,0.936762711436,1,1
0,9,0,662,0.0460784313725,0.953921568627,1,1
0,9,0,884,0.140390405106,0.859609594894,1,1
0,9,0,575,0.313761348977,0.686238651023,1,1
0,9,0,461,0.763904754262,0.236095245738,0,1
0,9,0,739,0.146147460272,0.853852539728,1,1
% 
% 
%