% Python_3.6.0.
% Sklearn_0.18.1.
% NumPy_1.13.0.
% SciPy_0.19.1.
% Fri Jul 21 03:49:53 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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0,9,0,485,0.0655852223331,0.934414777667,1,1
0,9,0,707,0.107813201181,0.892186798819,1,1
0,9,0,501,0.025819528465,0.974180471535,1,1
0,9,0,104,0.0541503968168,0.945849603183,1,1
0,9,0,213,0.0258120357405,0.974187964259,1,1
0,9,0,429,0.0,1.0,1,1
0,9,0,757,0.394716578445,0.605283421555,1,1
0,9,0,302,0.0181595280722,0.981840471928,1,1
0,9,0,841,0.00697597402597,0.993024025974,1,1
0,9,0,121,0.0243873446815,0.975612655319,1,1
0,9,0,878,0.2901117002,0.7098882998,1,1
0,9,0,174,0.0957738410311,0.904226158969,1,1
0,9,0,18,0.132798485311,0.867201514689,1,1
0,9,0,11,0.472421312519,0.527578687481,1,1
0,9,0,472,0.709302027034,0.290697972966,0,1
0,9,0,584,0.730189324847,0.269810675153,0,1
0,9,0,576,0.622969889935,0.377030110065,0,1
0,9,0,503,0.029831523411,0.970168476589,1,1
0,9,0,206,0.0532061970384,0.946793802962,1,1
0,9,0,132,0.0207759713716,0.979224028628,1,1
0,9,0,984,0.381815818713,0.618184181287,1,1
0,9,0,909,0.163641237089,0.836358762911,1,1
0,9,0,492,0.211528324174,0.788471675826,1,1
0,9,0,937,0.0704226873825,0.929577312618,1,1
0,9,0,408,0.0,1.0,1,1
0,9,0,892,0.0830769821277,0.916923017872,1,1
0,9,0,52,0.0493951465201,0.95060485348,1,1
0,9,0,542,0.421091379048,0.578908620952,1,1
0,9,0,239,0.0181595280722,0.981840471928,1,1
0,9,0,816,0.0139275638155,0.986072436185,1,1
0,9,0,82,0.0439458123605,0.95605418764,1,1
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0,9,0,516,0.0386597326745,0.961340267325,1,1
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0,9,0,448,0.209574773189,0.790425226811,1,1
0,9,0,846,0.00640401337793,0.993595986622,1,1
0,9,0,217,0.109785726197,0.890214273803,1,1
0,9,0,983,0.469923251046,0.530076748954,1,1
0,9,0,362,0.00128205128205,0.998717948718,1,1
0,9,0,356,0.0181595280722,0.981840471928,1,1
0,9,0,85,0.0439458123605,0.95605418764,1,1
0,9,0,22,0.0226709811824,0.977329018818,1,1
0,9,0,190,0.035961677734,0.964038322266,1,1
0,9,0,92,0.0631454858538,0.936854514146,1,1
0,9,0,941,0.234077657818,0.765922342182,1,1
0,9,0,549,0.101383366011,0.898616633989,1,1
0,9,0,716,0.0729071442058,0.927092855794,1,1
0,9,0,299,0.0,1.0,1,1
0,9,0,551,0.0473592342342,0.952640765766,1,1
0,9,0,661,0.266220906899,0.733779093101,1,1
0,9,0,102,0.0428473158807,0.957152684119,1,1
0,9,0,1010,0.460397317803,0.539602682197,1,1
0,9,0,530,0.15175221948,0.84824778052,1,1
0,9,0,290,0.000952380952381,0.999047619048,1,1
0,9,0,208,0.0532061970384,0.946793802962,1,1
0,9,0,988,0.32890582416,0.67109417584,1,1
0,9,0,665,0.0902658431807,0.909734156819,1,1
0,9,0,803,0.00806324110672,0.991936758893,1,1
0,9,0,447,0.533375297956,0.466624702044,0,1
0,9,0,786,0.0251756575205,0.97482434248,1,1
0,9,0,381,0.0,1.0,1,1
0,9,0,181,0.0890611223292,0.910938877671,1,1
0,9,0,34,0.0078100674224,0.992189932578,1,1
0,9,0,735,0.177231272399,0.822768727601,1,1
0,9,0,148,0.00320401337793,0.996795986622,1,1
0,9,0,98,0.111999469427,0.888000530573,1,1
0,9,0,662,0.0527841149255,0.947215885075,1,1
0,9,0,884,0.143387633972,0.856612366028,1,1
0,9,0,575,0.662639861903,0.337360138097,0,1
0,9,0,461,0.737063304087,0.262936695913,0,1
0,9,0,739,0.203049742234,0.796950257766,1,1
% 
% 
%