% Python_3.6.0.
% Sklearn_0.18.1.
% NumPy_1.13.0.
% SciPy_0.19.1.
% Thu Jul 20 19:58:15 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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0,9,0,669,0.03,0.97,1,1
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0,9,0,914,0.0607950693942,0.939204930606,1,1
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0,9,0,766,0.131620114703,0.868379885297,1,1
0,9,0,592,0.192274225117,0.807725774883,1,1
0,9,0,363,0.0,1.0,1,1
0,9,0,591,0.174963880289,0.825036119711,1,1
0,9,0,485,0.0456580368361,0.954341963164,1,1
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0,9,0,104,0.0964453527788,0.903554647221,1,1
0,9,0,213,0.0234087301587,0.976591269841,1,1
0,9,0,429,0.0043908045977,0.995609195402,1,1
0,9,0,757,0.347635739529,0.652364260471,1,1
0,9,0,302,0.002,0.998,1,1
0,9,0,841,0.00644444444444,0.993555555556,1,1
0,9,0,121,0.0567653108161,0.943234689184,1,1
0,9,0,878,0.175540487795,0.824459512205,1,1
0,9,0,174,0.0854088704559,0.914591129544,1,1
0,9,0,18,0.0914182327329,0.908581767267,1,1
0,9,0,11,0.321203533323,0.678796466677,1,1
0,9,0,472,0.750020851492,0.249979148508,0,1
0,9,0,584,0.153225785051,0.846774214949,1,1
0,9,0,576,0.119821844324,0.880178155676,1,1
0,9,0,503,0.0338626775272,0.966137322473,1,1
0,9,0,206,0.0435935990338,0.956406400966,1,1
0,9,0,132,0.00266666666667,0.997333333333,1,1
0,9,0,984,0.232750341909,0.767249658091,1,1
0,9,0,909,0.117481938028,0.882518061972,1,1
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0,9,0,937,0.0333344527924,0.966665547208,1,1
0,9,0,408,0.00869805097451,0.991301949025,1,1
0,9,0,892,0.0679061051268,0.932093894873,1,1
0,9,0,52,0.154990408831,0.845009591169,1,1
0,9,0,542,0.222630440615,0.777369559385,1,1
0,9,0,239,0.005,0.995,1,1
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0,9,0,554,0.0119175027871,0.988082497213,1,1
0,9,0,448,0.228680826142,0.771319173858,1,1
0,9,0,846,0.00952941176471,0.990470588235,1,1
0,9,0,217,0.0283258031379,0.971674196862,1,1
0,9,0,983,0.162623986627,0.837376013373,1,1
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0,9,0,356,0.0,1.0,1,1
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0,9,0,22,0.00658333333333,0.993416666667,1,1
0,9,0,190,0.0180931372549,0.981906862745,1,1
0,9,0,92,0.105082083036,0.894917916964,1,1
0,9,0,941,0.188865448997,0.811134551003,1,1
0,9,0,549,0.184458021745,0.815541978255,1,1
0,9,0,716,0.126442294772,0.873557705228,1,1
0,9,0,299,0.0,1.0,1,1
0,9,0,551,0.134579569976,0.865420430024,1,1
0,9,0,661,0.142108093417,0.857891906583,1,1
0,9,0,102,0.0836607608766,0.916339239123,1,1
0,9,0,1010,0.146280029847,0.853719970153,1,1
0,9,0,530,0.0942663345275,0.905733665472,1,1
0,9,0,290,0.0193333333333,0.980666666667,1,1
0,9,0,208,0.0435935990338,0.956406400966,1,1
0,9,0,988,0.206074886721,0.793925113279,1,1
0,9,0,665,0.00615384615385,0.993846153846,1,1
0,9,0,803,0.023051454278,0.976948545722,1,1
0,9,0,447,0.398147755427,0.601852244573,1,1
0,9,0,786,0.01575,0.98425,1,1
0,9,0,381,0.00466666666667,0.995333333333,1,1
0,9,0,181,0.0818280914269,0.918171908573,1,1
0,9,0,34,0.00719306184012,0.99280693816,1,1
0,9,0,735,0.295143337388,0.704856662612,1,1
0,9,0,148,0.00288888888889,0.997111111111,1,1
0,9,0,98,0.0938862948455,0.906113705154,1,1
0,9,0,662,0.22817708534,0.77182291466,1,1
0,9,0,884,0.116702256201,0.883297743799,1,1
0,9,0,575,0.24306498806,0.75693501194,1,1
0,9,0,461,0.722909945787,0.277090054213,0,1
0,9,0,739,0.310473731479,0.689526268521,1,1
% 
% 
%