% Python_3.6.0.
% Sklearn_0.18.1.
% NumPy_1.13.0.
% SciPy_0.19.1.
% Sat Aug 12 04:48:56 2017
% Created by run_task()
@RELATION openml_task_4_predictions

@ATTRIBUTE repeat NUMERIC
@ATTRIBUTE fold NUMERIC
@ATTRIBUTE sample NUMERIC
@ATTRIBUTE row_id NUMERIC
@ATTRIBUTE confidence.bad NUMERIC
@ATTRIBUTE confidence.good NUMERIC
@ATTRIBUTE prediction {bad, good}
@ATTRIBUTE correct {bad, good}

@DATA
0,0,0,41,0.26894142137,0.73105857863,good,bad
0,0,0,31,0.26894142137,0.73105857863,good,bad
0,0,0,54,0.26894142137,0.73105857863,good,good
0,0,0,13,0.26894142137,0.73105857863,good,good
0,0,0,10,0.26894142137,0.73105857863,good,good
0,0,0,2,0.73105857863,0.26894142137,bad,good
0,1,0,36,0.73105857863,0.26894142137,bad,bad
0,1,0,32,0.73105857863,0.26894142137,bad,bad
0,1,0,16,0.73105857863,0.26894142137,bad,good
0,1,0,22,0.26894142137,0.73105857863,good,good
0,1,0,46,0.26894142137,0.73105857863,good,good
0,1,0,9,0.26894142137,0.73105857863,good,good
0,2,0,25,0.73105857863,0.26894142137,bad,bad
0,2,0,33,0.73105857863,0.26894142137,bad,bad
0,2,0,50,0.26894142137,0.73105857863,good,good
0,2,0,20,0.26894142137,0.73105857863,good,good
0,2,0,3,0.26894142137,0.73105857863,good,good
0,2,0,7,0.26894142137,0.73105857863,good,good
0,3,0,37,0.26894142137,0.73105857863,good,bad
0,3,0,43,0.73105857863,0.26894142137,bad,bad
0,3,0,26,0.26894142137,0.73105857863,good,good
0,3,0,51,0.73105857863,0.26894142137,bad,good
0,3,0,55,0.26894142137,0.73105857863,good,good
0,3,0,52,0.26894142137,0.73105857863,good,good
0,4,0,40,0.73105857863,0.26894142137,bad,bad
0,4,0,18,0.73105857863,0.26894142137,bad,bad
0,4,0,1,0.26894142137,0.73105857863,good,good
0,4,0,24,0.26894142137,0.73105857863,good,good
0,4,0,47,0.26894142137,0.73105857863,good,good
0,4,0,19,0.26894142137,0.73105857863,good,good
0,5,0,45,0.73105857863,0.26894142137,bad,bad
0,5,0,35,0.73105857863,0.26894142137,bad,bad
0,5,0,4,0.26894142137,0.73105857863,good,good
0,5,0,0,0.26894142137,0.73105857863,good,good
0,5,0,53,0.26894142137,0.73105857863,good,good
0,5,0,30,0.26894142137,0.73105857863,good,good
0,6,0,34,0.73105857863,0.26894142137,bad,bad
0,6,0,17,0.73105857863,0.26894142137,bad,bad
0,6,0,49,0.26894142137,0.73105857863,good,good
0,6,0,39,0.26894142137,0.73105857863,good,good
0,6,0,14,0.26894142137,0.73105857863,good,good
0,6,0,6,0.26894142137,0.73105857863,good,good
0,7,0,42,0.73105857863,0.26894142137,bad,bad
0,7,0,38,0.73105857863,0.26894142137,bad,bad
0,7,0,27,0.26894142137,0.73105857863,good,good
0,7,0,5,0.73105857863,0.26894142137,bad,good
0,7,0,28,0.26894142137,0.73105857863,good,good
0,8,0,12,0.73105857863,0.26894142137,bad,bad
0,8,0,29,0.73105857863,0.26894142137,bad,bad
0,8,0,15,0.26894142137,0.73105857863,good,good
0,8,0,8,0.26894142137,0.73105857863,good,good
0,8,0,56,0.26894142137,0.73105857863,good,good
0,9,0,21,0.73105857863,0.26894142137,bad,bad
0,9,0,44,0.73105857863,0.26894142137,bad,bad
0,9,0,48,0.26894142137,0.73105857863,good,good
0,9,0,23,0.26894142137,0.73105857863,good,good
0,9,0,11,0.26894142137,0.73105857863,good,good
% 
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