% Python_3.8.18.
% Sklearn_1.3.2.
% NumPy_1.23.5.
% SciPy_1.10.1.
% Thu Jan 11 10:55:14 2024
% Created by run_flow_on_task
@RELATION openml_task_307_predictions

@ATTRIBUTE repeat NUMERIC
@ATTRIBUTE fold NUMERIC
@ATTRIBUTE sample NUMERIC
@ATTRIBUTE row_id NUMERIC
@ATTRIBUTE prediction {no, yes}
@ATTRIBUTE correct {no, yes}
@ATTRIBUTE confidence.no NUMERIC
@ATTRIBUTE confidence.yes NUMERIC

@DATA
0,0,0,293,no,no,0.9663403218264044,0.03365967817359548
0,0,0,102,no,no,0.9663403218264044,0.03365967817359548
0,0,0,67,no,no,0.58,0.42
0,0,0,147,no,no,0.68,0.32
0,0,0,164,no,no,0.9663403218264044,0.03365967817359548
0,0,0,396,no,no,0.99,0.01
0,0,0,118,no,no,0.86,0.14
0,0,0,26,yes,no,0.21,0.79
0,0,0,360,yes,no,0.38,0.62
0,0,0,72,no,no,0.9983333333333333,0.0016666666666666666
0,0,0,85,yes,no,0.41,0.59
0,0,0,174,no,no,0.9966666666666667,0.003333333333333333
0,0,0,250,yes,no,0.44,0.56
0,0,0,60,no,no,1.0,0.0
0,0,0,297,no,no,0.99,0.01
0,0,0,83,no,no,0.85,0.15
0,0,0,412,no,no,0.99,0.01
0,0,0,11,no,no,0.9884928229665071,0.011507177033492822
0,0,0,290,no,no,0.9987044534412955,0.0012955465587044534
0,0,0,205,no,no,0.64,0.36
0,0,0,182,no,no,0.99,0.01
0,0,0,47,no,no,0.9929761904761905,0.007023809523809523
0,0,0,417,no,no,0.56,0.44
0,0,0,133,no,no,0.97595757020757,0.024042429792429796
0,0,0,255,no,no,0.9548935802456233,0.045106419754376015
0,0,0,49,no,no,0.94,0.06
0,0,0,253,no,no,0.9548935802456233,0.045106419754376015
0,0,0,53,no,no,0.87,0.13
0,0,0,258,no,no,0.9871193068340812,0.012880693165918474
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0,0,0,109,no,no,0.9548935802456233,0.045106419754376015
0,0,0,69,no,no,0.8689126984126984,0.13108730158730159
0,0,0,318,no,no,0.9775000000000001,0.0225
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0,0,0,384,no,no,1.0,0.0
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0,0,0,188,no,no,1.0,0.0
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0,0,0,194,no,no,0.7,0.3
0,0,0,266,no,no,0.99,0.01
0,0,0,105,no,no,0.9989473684210526,0.0010526315789473684
0,0,0,398,no,no,0.9,0.1
0,0,0,493,no,yes,0.76,0.24
0,0,0,466,yes,yes,0.38,0.62
0,0,0,453,no,yes,0.77,0.23
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0,0,0,465,no,yes,0.77,0.23
0,0,0,501,no,yes,0.68,0.32
0,0,0,463,no,yes,0.8,0.2
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0,0,0,443,yes,yes,0.49,0.51
0,0,0,459,no,yes,0.61,0.39
0,1,0,32,no,no,0.68,0.32
0,1,0,254,no,no,0.9949326325848066,0.005067367415193501
0,1,0,324,no,no,0.62,0.38
0,1,0,138,no,no,0.9652120698144347,0.03478793018556512
0,1,0,123,no,no,0.720023837273837,0.27997616272616255
0,1,0,288,no,no,0.94,0.06
0,1,0,291,no,no,0.9993220338983051,0.0006779661016949153
0,1,0,93,no,no,0.9652120698144347,0.03478793018556512
0,1,0,303,no,no,0.99,0.01
0,1,0,420,no,no,0.66,0.34
0,1,0,106,yes,no,0.48,0.52
0,1,0,117,no,no,0.720023837273837,0.27997616272616255
0,1,0,56,no,no,0.99,0.01
0,1,0,247,no,no,0.817281746031746,0.182718253968254
0,1,0,305,no,no,1.0,0.0
0,1,0,346,no,no,0.8850209235209234,0.11497907647907643
0,1,0,9,no,no,1.0,0.0
0,1,0,347,no,no,0.8821042568542566,0.1178957431457431
0,1,0,218,no,no,0.9652120698144347,0.03478793018556512
0,1,0,377,no,no,0.97,0.03
0,1,0,406,no,no,0.98,0.02
0,1,0,282,no,no,0.73,0.27
0,1,0,416,no,no,0.6,0.4
0,1,0,280,no,no,1.0,0.0
0,1,0,219,no,no,0.9652120698144347,0.03478793018556512
0,1,0,29,no,no,1.0,0.0
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0,1,0,25,no,no,0.8821042568542566,0.1178957431457431
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0,1,0,482,yes,yes,0.18,0.82
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0,1,0,467,no,yes,0.64,0.36
0,1,0,428,yes,yes,0.12,0.88
0,1,0,509,no,yes,0.68,0.32
0,1,0,3,yes,yes,0.18,0.82
0,1,0,483,no,yes,0.52,0.48
0,1,0,512,no,yes,1.0,0.0
0,2,0,191,no,no,1.0,0.0
0,2,0,401,no,no,0.95,0.05
0,2,0,392,yes,no,0.16,0.84
0,2,0,341,no,no,0.95,0.05
0,2,0,197,yes,no,0.27,0.73
0,2,0,28,no,no,0.96,0.04
0,2,0,365,yes,no,0.45,0.55
0,2,0,160,no,no,0.66,0.34
0,2,0,139,no,no,0.98,0.02
0,2,0,339,no,no,0.93,0.07
0,2,0,351,no,no,1.0,0.0
0,2,0,320,no,no,0.9886004197816132,0.011399580218386609
0,2,0,342,no,no,0.985,0.015
0,2,0,363,yes,no,0.06,0.94
0,2,0,17,no,no,0.99,0.01
0,2,0,112,no,no,0.954161459571787,0.04583854042821287
0,2,0,149,no,no,0.85,0.15
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0,2,0,4,yes,yes,0.02,0.98
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0,2,0,2,yes,yes,0.22,0.78
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0,3,0,80,no,no,0.9113617591558767,0.08863824084412318
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0,3,0,345,no,no,0.95,0.05
0,3,0,73,no,no,0.9760414070996041,0.023958592900395904
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0,3,0,86,no,no,0.9715,0.0285
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