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Created April 4, 2023 16:21
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Output of autorank (including Nemenyi test) of the positivity experiments
Raw
benchmark120_seeds0-9_test_rankings.csv
method meanrank median mad ci_lower ci_upper effect_size magnitude
0 prop clip percentile_decision_tree_tuned_0.5 198.54285714285714 0.0 0.0 0.0 0.5515 large
1 IBM consistency_sep_rf_sklearn_0.05 197.13571428571427 0.0085 0.0085 0.0 0.564 -0.9538739797471302 large
2 IBM consistency_rf_flaml_0.05 197.125 0.008 0.008 0.0 0.562 -0.9538739797471303 large
3 prop clip_xgboost_flaml_calib_0.3 197.075 0.00275 0.00275 0.0 0.5675 -0.9538739797471301 large
4 IBM consistency_rf_sklearn_0.05 196.90535714285716 0.007 0.007 0.0 0.565 -0.9538739797471302 large
5 IBM consistency_sep_rf_flaml_0.05 196.87321428571428 0.01 0.01 0.0 0.565 -0.9538739797471302 large
6 prop clip_lgbm_calib_0.3 195.74821428571428 0.002 0.002 0.0 0.5665 -0.9538739797471303 large
7 IBM consistency_rf_flaml_0.25 194.10535714285714 0.03125 0.03125 0.0 0.5805 -0.9538739797471301 large
8 IBM consistency_sep_rf_flaml_0.25 194.09285714285716 0.03125 0.03125 0.0 0.5805 -0.9538739797471301 large
9 IBM consistency_rf_sklearn_0.25 194.01964285714286 0.03125 0.03125 0.0 0.5805 -0.9538739797471301 large
10 IBM consistency_sep_rf_sklearn_0.25 193.90178571428572 0.03125 0.03125 0.0 0.5805 -0.9538739797471301 large
11 prop clip_lgbm_calib_0.2 193.07142857142858 0.01175 0.01175 0.0 0.584 -0.9538739797471301 large
12 prop clip_lgbm_flaml_calib_0.3 192.80178571428573 0.004 0.004 0.0 0.5715 -0.9538739797471303 large
13 prop clip_xgboost_calib_0.3 192.67678571428573 0.004 0.004 0.0 0.57 -0.9538739797471303 large
14 prop clip_xgboost_flaml_calib_0.2 192.52678571428572 0.009000000000000001 0.009000000000000001 0.0 0.581 -0.9538739797471301 large
15 prop clip_xgboost_flaml_0.3 190.50357142857143 0.04325 0.04325 0.002 0.565 -0.9538739797471301 large
16 prop clip_decision_tree_tuned_0.3 190.37678571428572 0.0035 0.0035 0.0005 0.5515 -0.9538739797471302 large
17 prop clip_rf_flaml_calib_0.3 190.16964285714286 0.00425 0.00425 0.0 0.5845 -0.9538739797471302 large
18 prop clip_lr_calib_0.3 189.175 0.0695 0.0695 0.0 0.5515 -0.9538739797471302 large
19 prop clip_rf_sklearn_calib_0.3 189.14285714285714 0.0072499999999999995 0.0072499999999999995 0.0 0.584 -0.9538739797471302 large
20 IBM consistency_rf_sklearn_0.5 188.71785714285716 0.042749999999999996 0.042749999999999996 0.0 0.583 -0.95387397974713 large
21 IBM consistency_rf_flaml_0.5 188.5767857142857 0.042749999999999996 0.042749999999999996 0.0 0.583 -0.95387397974713 large
22 prop clip_lgbm_flaml_calib_0.2 188.37857142857143 0.00875 0.00875 0.0 0.5835 -0.9538739797471302 large
23 IBM consistency_sep_rf_sklearn_0.5 188.32142857142858 0.042749999999999996 0.042749999999999996 0.0 0.583 -0.95387397974713 large
24 IBM consistency_sep_rf_flaml_0.5 188.27142857142857 0.042749999999999996 0.042749999999999996 0.0 0.583 -0.95387397974713 large
25 prop clip_linear_svm_calib_0.3 188.05714285714285 0.074 0.074 0.0 0.5725 -0.9538739797471302 large
26 prop clip_xgboost_calib_0.2 187.80714285714285 0.0245 0.0245 0.0 0.5825 -0.9538739797471301 large
27 IBM consistency_rf_flaml_0.75 187.56428571428572 0.04325 0.04325 0.0 0.583 -0.9538739797471301 large
28 IBM consistency_rf_sklearn_0.75 187.54285714285714 0.043 0.043 0.0 0.583 -0.95387397974713 large
29 prop clip_decision_tree_tuned_0.2 186.6017857142857 0.010499999999999999 0.010499999999999999 0.0015 0.5545 -0.9538739797471302 large
30 prop clip_linear_svm_calib_0.2 186.4142857142857 0.11775 0.11775 0.0 0.668 -0.9538739797471302 large
31 prop clip_lgbm_flaml_0.3 186.24821428571428 0.0215 0.0215 0.0045 0.572 -0.95387397974713 large
32 prop clip_lgbm_0.3 185.88214285714287 0.011 0.011 0.005 0.562 -0.9538739797471301 large
33 prop clip_rf_flaml_calib_0.2 185.69821428571427 0.012 0.012 0.0 0.5855 -0.9538739797471301 large
34 IBM consistency_rf_sklearn_0.95 185.64285714285714 0.0435 0.0435 0.001 0.5835 -0.9538739797471301 large
35 IBM consistency_rf_flaml_0.95 185.5875 0.0435 0.0435 0.0005 0.5835 -0.9538739797471301 large
36 prop clip_lr_calib_0.2 185.43392857142857 0.12925 0.12925 0.0 0.5515 -0.9538739797471302 large
37 IBM consistency_rf_sklearn_0.975 184.66607142857143 0.04375 0.04375 0.002 0.5835 -0.9538739797471301 large
38 IBM consistency_rf_flaml_0.975 184.65178571428572 0.04375 0.04375 0.0015 0.5835 -0.9538739797471301 large
39 prop clip_xgboost_0.3 184.6392857142857 0.023 0.023 0.014 0.5675 -0.9538739797471301 large
40 prop clip_rf_flaml_0.3 184.55357142857142 0.08 0.08 0.0075 0.585 -0.9538739797471302 large
41 IBM consistency_rf_sklearn_0.99 183.95 0.044 0.044 0.003 0.5835 -0.9538739797471301 large
42 IBM consistency_rf_flaml_0.99 183.81428571428572 0.044 0.044 0.0025 0.584 -0.9538739797471301 large
43 prop clip_rf_sklearn_calib_0.2 183.53035714285716 0.03875 0.03875 0.0 0.585 -0.9538739797471302 large
44 IBM consistency_rf_sklearn_1.0 183.01607142857142 0.04425 0.04425 0.005 0.5835 -0.9538739797471301 large
45 prop clip_xgboost_flaml_0.2 182.5232142857143 0.10825 0.10825 0.005 0.5815 -0.9538739797471302 large
46 IBM consistency_rf_flaml_1.0 181.91071428571428 0.051000000000000004 0.051000000000000004 0.0055 0.586 -0.9538739797471301 large
47 prop clip_lr_0.3 179.25178571428572 0.3265 0.3245 0.1405 0.542 -0.9597530181431063 large
48 prop clip_lgbm_0.2 178.78214285714284 0.052 0.052 0.0315 0.586 -0.9538739797471302 large
49 prop clip_lgbm_flaml_0.2 178.63571428571427 0.07775 0.07775 0.009 0.584 -0.9538739797471302 large
50 prop clip_rf_sklearn_0.3 177.16607142857143 0.084 0.084 0.013 0.5855 -0.9538739797471301 large
51 prop clip_xgboost_0.2 176.48392857142858 0.0685 0.0685 0.0415 0.583 -0.9538739797471302 large
52 prop clip_rf_flaml_0.2 174.25 0.148 0.1475 0.0225 0.5865 -0.9571074508649169 large
53 prop clip_lr_0.2 173.83928571428572 0.466 0.329 0.1505 0.568 -1.3510798618910718 large
54 IBM consistency_sep_rf_flaml_0.75 173.66964285714286 0.11 0.11 0.0195 0.5885 -0.9538739797471302 large
55 prop clip_lr_calib_0.1 168.74464285714285 0.567 0.3755 0.227 0.753 -1.4403370080336158 large
56 prop clip_xgboost_flaml_0.1 168.04464285714286 0.2755 0.2705 0.032 0.596 -0.9715056614430106 large
57 prop clip_linear_svm_calib_0.1 167.93214285714285 0.5782499999999999 0.3795 0.1985 0.771 -1.4534324869269513 large
58 IBM consistency_sep_rf_sklearn_0.75 165.37857142857143 0.1245 0.124 0.0345 0.5875 -0.9577202457944977 large
59 prop clip_lgbm_flaml_0.1 164.19285714285715 0.312 0.3025 0.047 0.616 -0.9838303526648087 large
60 prop clip_rf_sklearn_0.2 162.85892857142858 0.15425 0.15225 0.1045 0.613 -0.9664043440131023 large
61 Vianai_rf_sklearn_calib_0.1 160.1017857142857 0.358 0.26549999999999996 0.167 0.613 -1.2862029557418933 large
62 Vianai_rf_sklearn_0.1 160.1017857142857 0.358 0.26549999999999996 0.167 0.613 -1.2862029557418933 large
63 prop clip_xgboost_flaml_calib_0.1 159.52142857142857 0.51125 0.47525 0.1455 0.799 -1.0261295573818419 large
64 Vianai_rf_sklearn_0.05 159.21785714285716 0.37324999999999997 0.25975 0.1815 0.613 -1.370677431917676 large
65 Vianai_rf_sklearn_calib_0.05 159.21785714285716 0.37324999999999997 0.25975 0.1815 0.613 -1.370677431917676 large
66 prop clip_lgbm_calib_0.1 158.28571428571428 0.543 0.4485 0.141 0.809 -1.1548574604296358 large
67 prop clip_xgboost_0.1 157.975 0.3475 0.34249999999999997 0.137 0.632 -0.9677991473346796 large
68 prop clip_lr_0.1 157.2732142857143 0.5902499999999999 0.27525 0.4045 0.731 -2.045500877550385 large
69 prop clip_lgbm_0.1 157.0 0.37375 0.362 0.2385 0.657 -0.9848353589240053 large
70 Vianai_rf_sklearn_0.01 156.75535714285715 0.41925 0.26725 0.2785 0.619 -1.4963953826341791 large
71 Vianai_rf_sklearn_calib_0.01 156.75535714285715 0.41925 0.26725 0.2785 0.619 -1.4963953826341791 large
72 prop clip_decision_tree_tuned_0.1 155.4625 0.4455 0.4445 0.0565 0.819 -0.9560199279580348 large
73 prop clip_xgboost_calib_0.1 154.84107142857144 0.5265 0.45400000000000007 0.13 0.8055 -1.1061996703455153 large
74 Vianai_rf_flaml_0.1 154.82142857142858 0.42625 0.30975 0.1765 0.716 -1.3126352990063412 large
75 Vianai_rf_flaml_calib_0.1 154.82142857142858 0.42625 0.30975 0.1765 0.716 -1.3126352990063412 large
76 prop clip_lgbm_flaml_calib_0.1 154.35714285714286 0.52275 0.46074999999999994 0.142 0.8265 -1.0822303264521158 large
77 Vianai_rf_sklearn_calib_0.001 154.16785714285714 0.45675 0.2535 0.298 0.6285 -1.7186664309645037 large
78 Vianai_rf_sklearn_0.001 154.16785714285714 0.45675 0.2535 0.298 0.6285 -1.7186664309645037 large
79 prop clip_rf_flaml_calib_0.1 153.80714285714285 0.5485 0.44725000000000004 0.1205 0.8195 -1.1698152663863628 large
80 Vianai_rf_flaml_0.05 153.18035714285713 0.465 0.3175 0.2045 0.7165 -1.3970122852989466 large
81 Vianai_rf_flaml_calib_0.05 153.18035714285713 0.465 0.3175 0.2045 0.7165 -1.3970122852989466 large
82 Vianai_rf_sklearn_calib_0.0001 152.81964285714287 0.47624999999999995 0.24824999999999994 0.3175 0.6855 -1.8299395079741019 large
83 Vianai_rf_sklearn_0.0001 152.81964285714287 0.47624999999999995 0.24824999999999994 0.3175 0.6855 -1.8299395079741019 large
84 prop clip_rf_sklearn_calib_0.1 152.50535714285715 0.5435000000000001 0.44200000000000006 0.131 0.8095 -1.1729197013406454 large
85 Vianai_lgbm_flaml_calib_0.1 152.33928571428572 0.48924999999999996 0.39949999999999997 0.1425 0.7855 -1.1681673206289946 large
86 Vianai_lgbm_flaml_0.1 152.33928571428572 0.48924999999999996 0.39949999999999997 0.1425 0.7855 -1.1681673206289946 large
87 Vianai_lgbm_flaml_0.05 152.06071428571428 0.4955 0.39575000000000005 0.1565 0.7895 -1.194300838824265 large
88 Vianai_lgbm_flaml_calib_0.05 152.06071428571428 0.4955 0.39575000000000005 0.1565 0.7895 -1.194300838824265 large
89 Vianai_lgbm_flaml_0.01 151.6732142857143 0.488 0.38450000000000006 0.178 0.759 -1.210638497052274 large
90 Vianai_lgbm_flaml_calib_0.01 151.6732142857143 0.488 0.38450000000000006 0.178 0.759 -1.210638497052274 large
91 Vianai_rf_flaml_calib_0.01 150.66785714285714 0.49124999999999996 0.312 0.335 0.755 -1.501892924842236 large
92 Vianai_rf_flaml_0.01 150.66785714285714 0.49124999999999996 0.312 0.335 0.755 -1.501892924842236 large
93 Vianai_lgbm_flaml_0.001 150.36785714285713 0.49 0.383 0.2065 0.788 -1.2203609662561195 large
94 Vianai_lgbm_flaml_calib_0.001 150.36785714285713 0.49 0.383 0.2065 0.788 -1.2203609662561195 large
95 Vianai_lgbm_flaml_0.0001 150.04285714285714 0.49 0.38000000000000006 0.221 0.788 -1.2299953949370885 large
96 Vianai_lgbm_flaml_calib_0.0001 150.04285714285714 0.49 0.38000000000000006 0.221 0.788 -1.2299953949370885 large
97 prop clip_lgbm_flaml_0.05 149.37142857142857 0.5972500000000001 0.37449999999999994 0.1325 0.763 -1.5212316005446556 large
98 prop clip_rf_flaml_0.1 146.76785714285714 0.524 0.41975 0.2545 0.698 -1.190780143865387 large
99 Vianai_rf_flaml_0.001 146.64285714285714 0.5297499999999999 0.28525 0.365 0.7815 -1.7714802481018128 large
100 Vianai_rf_flaml_calib_0.001 146.64285714285714 0.5297499999999999 0.28525 0.365 0.7815 -1.7714802481018128 large
101 prop clip_xgboost_flaml_0.05 146.0875 0.4625 0.4335 0.2085 0.6765 -1.017685618530675 large
102 Vianai_rf_flaml_calib_0.0001 145.74107142857142 0.56275 0.27375000000000005 0.365 0.789 -1.9608861446673875 large
103 Vianai_rf_flaml_0.0001 145.74107142857142 0.56275 0.27375000000000005 0.365 0.789 -1.9608861446673875 large
104 prop clip_rf_sklearn_0.1 144.2125 0.57175 0.32175 0.271 0.714 -1.695034803171474 large
105 prop clip_linear_svm_calib_0.05 142.75178571428572 0.7242500000000001 0.27574999999999994 0.401 0.9785 -2.505324496217078 large
106 prop clip_lr_calib_0.05 141.53035714285716 0.757 0.243 0.4045 0.964 -2.9715333443151337 large
107 prop clip_lr_0.05 139.2642857142857 0.79925 0.20074999999999998 0.438 0.903 -3.79767760056236 large
108 Vianai_xgboost_flaml_calib_0.1 138.65892857142856 0.476 0.38875 0.1895 0.785 -1.167958879381695 large
109 Vianai_xgboost_flaml_0.1 138.65892857142856 0.476 0.38875 0.1895 0.785 -1.167958879381695 large
110 Vianai_xgboost_flaml_calib_0.05 137.56785714285715 0.4905 0.38775000000000004 0.1895 0.785 -1.2066413592932748 large
111 Vianai_xgboost_flaml_0.05 137.56785714285715 0.4905 0.38775000000000004 0.1895 0.785 -1.2066413592932748 large
112 prop clip_xgboost_0.05 134.2982142857143 0.59675 0.345 0.301 0.789 -1.6499254997510142 large
113 Vianai_xgboost_flaml_calib_0.01 134.05 0.4905 0.376 0.222 0.785 -1.2443489017711897 large
114 Vianai_xgboost_flaml_0.01 134.05 0.4905 0.376 0.222 0.785 -1.2443489017711897 large
115 Vianai_lgbm_calib_0.1 133.09464285714284 0.6479999999999999 0.3487500000000001 0.13 0.8625 -1.7723593946269247 large
116 Vianai_lgbm_0.1 133.09464285714284 0.6479999999999999 0.3487500000000001 0.13 0.8625 -1.7723593946269247 large
117 prop clip percentile_decision_tree_tuned_0.4 132.80892857142857 0.712 0.281 0.426 0.8705 -2.416933357935789 large
118 Vianai_lgbm_calib_0.05 131.90714285714284 0.6479999999999999 0.3487500000000001 0.1335 0.8625 -1.7723593946269247 large
119 Vianai_lgbm_0.05 131.90714285714284 0.6479999999999999 0.3487500000000001 0.1335 0.8625 -1.7723593946269247 large
120 prop clip_lgbm_0.05 131.7357142857143 0.76 0.20249999999999996 0.63 0.851 -3.5799714795447857 large
121 Vianai_xgboost_flaml_0.001 131.4625 0.489 0.35850000000000004 0.2515 0.783 -1.3011000727931563 large
122 Vianai_xgboost_flaml_calib_0.001 131.4625 0.489 0.35850000000000004 0.2515 0.783 -1.3011000727931563 large
123 IBM consistency_sep_rf_sklearn_0.95 131.20357142857142 0.6172500000000001 0.2809999999999999 0.4035 0.86 -2.095297914586891 large
124 Vianai_xgboost_flaml_calib_0.0001 131.13035714285715 0.4905 0.35800000000000004 0.259 0.783 -1.306913930351864 large
125 Vianai_xgboost_flaml_0.0001 131.13035714285715 0.4905 0.35800000000000004 0.259 0.783 -1.306913930351864 large
126 prop clip_rf_sklearn_0.05 131.08035714285714 0.5974999999999999 0.32250000000000006 0.411 0.879 -1.7672548927097986 large
127 Vianai_lgbm_calib_0.01 130.47857142857143 0.6499999999999999 0.3467500000000001 0.1445 0.864 -1.7880838841690967 large
128 Vianai_lgbm_0.01 130.47857142857143 0.6499999999999999 0.3467500000000001 0.1445 0.864 -1.7880838841690967 large
129 IBM consistency_sep_rf_sklearn_0.975 129.82142857142858 0.6205 0.34674999999999995 0.5085 0.85 -1.7069323848106546 large
130 prop clip_rf_flaml_0.05 129.75892857142858 0.68625 0.29425 0.378 0.937 -2.224625381823171 large
131 Vianai_lgbm_0.001 128.69642857142858 0.6515 0.3450000000000001 0.1565 0.866 -1.8013011530587106 large
132 Vianai_lgbm_calib_0.001 128.69642857142858 0.6515 0.3450000000000001 0.1565 0.866 -1.8013011530587106 large
133 IBM consistency_sep_rf_flaml_0.95 128.42857142857142 0.68875 0.29025 0.394 0.939 -2.263499409305205 large
134 IBM consistency_sep_rf_sklearn_0.99 127.60178571428571 0.6595 0.301 0.566 0.8375 -2.089966410774858 large
135 Vianai_lgbm_0.0001 127.14821428571429 0.65525 0.34125000000000005 0.181 0.8665 -1.831577802869764 large
136 Vianai_lgbm_calib_0.0001 127.14821428571429 0.65525 0.34125000000000005 0.181 0.8665 -1.831577802869764 large
137 prop clip_rf_sklearn_0.01 123.69642857142857 0.71475 0.20775 0.5865 0.84 -3.281739720935072 large
138 prop clip_rf_sklearn_0.005 123.43571428571428 0.71475 0.20800000000000002 0.5865 0.841 -3.2777953222320253 large
139 prop clip_rf_sklearn_0.001 123.03035714285714 0.71475 0.20800000000000002 0.5865 0.842 -3.2777953222320253 large
140 prop clip_rf_sklearn_0.0005 122.87142857142857 0.71475 0.20800000000000002 0.5865 0.843 -3.2777953222320253 large
141 prop clip_rf_sklearn_0.0001 122.8 0.71475 0.20775000000000005 0.5865 0.843 -3.281739720935071 large
142 IBM consistency_sep_rf_sklearn_1.0 122.40178571428571 0.716 0.20999999999999996 0.583 0.8325 -3.2522560452330724 large
143 prop clip_decision_tree_tuned_0.05 121.84821428571429 0.94 0.06000000000000005 0.5735 0.9865 -14.944025682705023 large
144 prop clip_lgbm_flaml_0.01 121.49285714285715 0.87475 0.11575000000000002 0.6275 0.938 -7.208650227073884 large
145 prop clip_linear_svm_calib_0.01 121.12142857142857 0.743 0.257 0.4485 0.9925 -2.7576979258837264 large
146 prop clip_lgbm_flaml_0.0001 121.06964285714285 0.731 0.269 0.444 1.0 -2.592125944963391 large
147 prop clip_lr_0.01 120.82857142857142 0.83925 0.16074999999999995 0.507 0.952 -4.980023250406092 large
148 IBM consistency_sep_rf_flaml_0.975 120.37321428571428 0.68375 0.29900000000000004 0.489 0.9105 -2.1813088082010035 large
149 prop clip_rf_flaml_0.001 119.66607142857143 0.8340000000000001 0.13325000000000004 0.7065 0.89 -5.970213126522374 large
150 prop clip_rf_flaml_0.0005 119.5375 0.8340000000000001 0.13325000000000004 0.7065 0.89 -5.970213126522374 large
151 prop clip_lgbm_flaml_0.0005 119.47857142857143 0.6785000000000001 0.3214999999999999 0.461 0.9885 -2.013074635329481 large
152 prop clip_rf_flaml_0.0001 119.34285714285714 0.8340000000000001 0.13324999999999992 0.7065 0.89 -5.970213126522379 large
153 IBM consistency_sep_rf_flaml_1.0 118.3125 0.8402499999999999 0.13424999999999998 0.706 0.8925 -5.970149806201311 large
154 Vianai_xgboost_0.1 118.20892857142857 0.79 0.20999999999999996 0.326 0.898 -3.588383066667776 large
155 Vianai_xgboost_calib_0.1 118.20892857142857 0.79 0.20999999999999996 0.326 0.898 -3.588383066667776 large
156 prop clip_lr_calib_0.01 118.09107142857142 0.805 0.19499999999999995 0.471 0.9745 -3.937787454853539 large
157 prop clip_lr_0.005 117.56607142857143 0.91725 0.08274999999999999 0.762 0.9745 -10.573304023239338 large
158 Vianai_xgboost_0.05 117.45178571428572 0.7907500000000001 0.20924999999999994 0.3275 0.898 -3.6046635578735646 large
159 Vianai_xgboost_calib_0.05 117.45178571428572 0.7907500000000001 0.20924999999999994 0.3275 0.898 -3.6046635578735646 large
160 prop clip_lr_0.0001 116.5875 0.9217500000000001 0.07824999999999993 0.6465 1.0 -11.236208828522914 large
161 prop clip_lr_0.0005 115.98392857142858 0.9255 0.07450000000000001 0.64 0.9985 -11.849803600751258 large
162 IBM consistency_sep_rf_flaml_0.99 115.93035714285715 0.7205 0.23824999999999996 0.608 0.8805 -2.8846430321418985 large
163 Vianai_xgboost_calib_0.01 115.70714285714286 0.7907500000000001 0.20924999999999994 0.3285 0.9005 -3.6046635578735646 large
164 Vianai_xgboost_0.01 115.70714285714286 0.7907500000000001 0.20924999999999994 0.3285 0.9005 -3.6046635578735646 large
165 prop clip_lr_0.001 115.47678571428571 0.92875 0.07125000000000004 0.629 0.9975 -12.433830999159953 large
166 prop clip_rf_flaml_0.01 115.23035714285714 0.728 0.23050000000000004 0.613 0.877 -3.012669228875968 large
167 prop clip_lgbm_flaml_0.005 114.67142857142858 0.865 0.13250000000000006 0.586 0.97 -6.227177301745412 large
168 prop clip_rf_flaml_0.005 113.96071428571429 0.7629999999999999 0.14199999999999996 0.701 0.8475 -5.125393285542678 large
169 Vianai_xgboost_calib_0.001 113.43392857142857 0.7907500000000001 0.20924999999999994 0.3285 0.9005 -3.6046635578735646 large
170 Vianai_xgboost_0.001 113.43392857142857 0.7907500000000001 0.20924999999999994 0.3285 0.9005 -3.6046635578735646 large
171 prop clip_xgboost_flaml_calib_0.05 112.60892857142858 0.99525 0.004750000000000032 0.6765 1.0 -199.86170070385788 large
172 Vianai_xgboost_0.0001 112.4125 0.7909999999999999 0.20900000000000007 0.335 0.9015 -3.610116353971194 large
173 Vianai_xgboost_calib_0.0001 112.4125 0.7909999999999999 0.20900000000000007 0.335 0.9015 -3.610116353971194 large
174 prop clip_lgbm_calib_0.05 111.60535714285714 0.9955 0.0044999999999999485 0.679 1.0 -211.01812151961752 large
175 prop clip_xgboost_calib_0.0005 111.51785714285714 1.0 0.0 0.4765 1.0 -inf large
176 prop clip_xgboost_calib_0.0001 111.51785714285714 1.0 0.0 0.4765 1.0 -inf large
177 prop clip_rf_flaml_calib_0.0001 111.35357142857143 1.0 0.0 0.4765 1.0 -inf large
178 prop clip_lgbm_calib_0.0001 111.35357142857143 1.0 0.0 0.4765 1.0 -inf large
179 prop clip_lgbm_calib_0.0005 111.35357142857143 1.0 0.0 0.4765 1.0 -inf large
180 prop clip_xgboost_flaml_calib_0.0005 111.35357142857143 1.0 0.0 0.4765 1.0 -inf large
181 prop clip_xgboost_flaml_calib_0.0001 111.35357142857143 1.0 0.0 0.4765 1.0 -inf large
182 prop clip_lgbm_flaml_calib_0.0001 111.25 1.0 0.0 0.4765 1.0 -inf large
183 prop clip_lgbm_flaml_calib_0.0005 111.24642857142857 1.0 0.0 0.4765 1.0 -inf large
184 prop clip_rf_sklearn_calib_0.0001 111.23928571428571 1.0 0.0 0.4765 1.0 -inf large
185 prop clip_rf_flaml_calib_0.0005 111.13392857142857 1.0 0.0 0.4765 1.0 -inf large
186 prop clip_lgbm_flaml_0.001 110.90357142857142 0.752 0.248 0.525 0.97 -2.8923920676203303 large
187 prop clip_linear_svm_calib_0.0001 110.35178571428571 1.0 0.0 0.566 1.0 -inf large
188 prop clip_lr_calib_0.0001 109.52321428571429 1.0 0.0 0.66 1.0 -inf large
189 prop clip_rf_sklearn_calib_0.0005 109.20892857142857 1.0 0.0 0.5595 1.0 -inf large
190 prop clip_rf_sklearn_calib_0.05 108.75535714285714 0.97275 0.027249999999999996 0.6955 0.9995 -34.05067573574389 large
191 prop clip_linear_svm_calib_0.0005 108.64642857142857 1.0 0.0 0.661 1.0 -inf large
192 prop clip_rf_flaml_calib_0.05 108.39107142857142 0.986 0.014000000000000012 0.6885 0.9995 -67.17998171647639 large
193 prop clip_linear_svm_calib_0.001 108.30357142857143 1.0 0.0 0.662 1.0 -inf large
194 prop clip_lgbm_flaml_calib_0.05 107.81964285714285 0.9945 0.005499999999999949 0.688 1.0 -172.47775870155084 large
195 prop clip_lr_calib_0.0005 106.52142857142857 0.99975 0.00024999999999997247 0.6865 1.0 -3814.5420450091938 large
196 prop clip_xgboost_calib_0.05 106.46071428571429 0.9995 0.0004999999999999449 0.6795 1.0 -1906.7940855147233 large
197 prop clip_xgboost_0.0001 105.8 0.85 0.15000000000000002 0.7365 0.999 -5.405285885233736 large
198 prop clip_lr_calib_0.001 105.75892857142857 0.999 0.0010000000000000009 0.722 1.0 -952.9201057673821 large
199 prop clip_linear_svm_calib_0.005 105.225 0.99725 0.00275000000000003 0.8515 1.0 -345.90939138284176 large
200 prop clip_lr_calib_0.005 104.76428571428572 0.97975 0.02024999999999999 0.8665 1.0 -46.151013909000056 large
201 prop clip_lgbm_0.01 100.60357142857143 0.9784999999999999 0.021500000000000075 0.675 0.9935 -43.412357636398305 large
202 prop clip_xgboost_flaml_0.0001 98.92142857142858 0.978 0.02200000000000002 0.855 1.0 -42.40403419057692 large
203 prop clip_lgbm_flaml_calib_0.001 98.85 1.0 0.0 0.859 1.0 -inf large
204 prop clip_lgbm_calib_0.001 95.23928571428571 1.0 0.0 0.9305 1.0 -inf large
205 prop clip percentile_decision_tree_tuned_0.3 94.59821428571429 0.8975 0.10250000000000004 0.772 0.9635 -8.352213627541943 large
206 prop clip_xgboost_flaml_0.0005 94.06964285714285 0.984 0.016000000000000014 0.9145 1.0 -58.663249754448444 large
207 prop clip_rf_flaml_calib_0.001 93.97678571428571 1.0 0.0 0.9145 1.0 -inf large
208 prop clip_xgboost_0.01 93.73392857142858 0.8532500000000001 0.14274999999999993 0.687 0.9715 -5.701526957752989 large
209 prop clip_rf_sklearn_calib_0.001 93.17321428571428 1.0 0.0 0.8675 1.0 -inf large
210 prop clip_xgboost_flaml_0.001 91.14285714285714 0.9895 0.010499999999999954 0.829 1.0 -89.89126694855136 large
211 Vianai_lr_calib_0.0001 89.30535714285715 0.99925 0.0007500000000000284 0.9645 1.0 -1270.8780990163782 large
212 Vianai_lr_0.0001 89.30535714285715 0.99925 0.0007500000000000284 0.9645 1.0 -1270.8780990163782 large
213 prop clip_xgboost_flaml_0.01 89.25 0.90575 0.09424999999999994 0.713 0.979 -9.166804850461153 large
214 Vianai_lr_calib_0.001 88.62857142857143 0.999 0.0010000000000000009 0.967 1.0 -952.9201057673821 large
215 Vianai_lr_0.001 88.62857142857143 0.999 0.0010000000000000009 0.967 1.0 -952.9201057673821 large
216 Vianai_lr_calib_0.05 87.2625 0.999 0.0010000000000000009 0.968 1.0 -952.9201057673821 large
217 Vianai_lr_0.05 87.2625 0.999 0.0010000000000000009 0.968 1.0 -952.9201057673821 large
218 Vianai_lr_calib_0.01 87.18571428571428 0.999 0.0010000000000000009 0.9675 1.0 -952.9201057673821 large
219 Vianai_lr_0.01 87.18571428571428 0.999 0.0010000000000000009 0.9675 1.0 -952.9201057673821 large
220 Vianai_linear_svm_calib_0.0001 87.05 0.99875 0.0012499999999999734 0.968 1.0 -762.1453098179733 large
221 Vianai_lr_calib_0.1 87.05 0.99875 0.0012499999999999734 0.968 1.0 -762.1453098179733 large
222 Vianai_linear_svm_calib_0.001 87.05 0.99875 0.0012499999999999734 0.968 1.0 -762.1453098179733 large
223 Vianai_linear_svm_calib_0.01 87.05 0.99875 0.0012499999999999734 0.968 1.0 -762.1453098179733 large
224 Vianai_lr_0.1 87.05 0.99875 0.0012499999999999734 0.968 1.0 -762.1453098179733 large
225 Vianai_linear_svm_calib_0.05 87.05 0.99875 0.0012499999999999734 0.968 1.0 -762.1453098179733 large
226 Vianai_linear_svm_calib_0.1 87.05 0.99875 0.0012499999999999734 0.968 1.0 -762.1453098179733 large
227 prop clip_xgboost_0.005 87.0 0.9255 0.07350000000000001 0.71 0.9865 -12.011025418448556 large
228 prop clip_xgboost_calib_0.001 86.69285714285714 1.0 0.0 0.961 1.0 -inf large
229 prop clip_lgbm_0.005 86.15357142857142 0.99 0.010000000000000009 0.6755 0.9975 -94.4335239949658 large
230 prop clip_xgboost_flaml_calib_0.001 86.00892857142857 1.0 0.0 0.961 1.0 -inf large
231 prop clip_rf_sklearn_calib_0.01 82.775 0.97325 0.02675000000000005 0.776 0.9995 -34.7049663846315 large
232 prop clip_xgboost_0.0005 81.4875 0.9430000000000001 0.056499999999999995 0.8985 0.9895 -15.920409962859184 large
233 prop clip_rf_flaml_calib_0.01 81.44285714285714 0.9882500000000001 0.011749999999999927 0.7995 0.9995 -80.22689025405167 large
234 prop clip_xgboost_0.001 81.15 0.9572499999999999 0.04225000000000012 0.9 0.9925 -21.6117364997145 large
235 prop clip_lgbm_flaml_calib_0.01 80.69285714285714 0.99375 0.006249999999999978 0.8855 1.0 -151.66596277979423 large
236 prop clip_decision_tree_tuned_0.01 80.2625 0.9744999999999999 0.025500000000000078 0.8345 0.9955 -36.45294875543433 large
237 prop clip percentile_decision_tree_tuned_0.2 80.13392857142857 0.944 0.05600000000000005 0.8725 0.9775 -16.07958994430875 large
238 prop clip_xgboost_flaml_0.005 78.99107142857143 0.9145 0.08550000000000002 0.8045 0.988 -10.202546836008775 large
239 prop clip percentile_decision_tree_tuned_0.1 73.58035714285714 0.971 0.029000000000000026 0.906 0.989 -31.93833221842974 large
240 prop clip percentile_decision_tree_tuned_0.05 72.91428571428571 0.971 0.029000000000000026 0.908 0.989 -31.93833221842974 large
241 prop clip percentile_decision_tree_tuned_0.01 72.89285714285714 0.971 0.029000000000000026 0.908 0.989 -31.93833221842974 large
242 prop clip percentile_decision_tree_tuned_0.0001 72.89285714285714 0.971 0.029000000000000026 0.908 0.989 -31.93833221842974 large
243 prop clip percentile_decision_tree_tuned_0.0005 72.89285714285714 0.971 0.029000000000000026 0.908 0.989 -31.93833221842974 large
244 prop clip percentile_decision_tree_tuned_0.001 72.89285714285714 0.971 0.029000000000000026 0.908 0.989 -31.93833221842974 large
245 prop clip percentile_decision_tree_tuned_0.005 72.89285714285714 0.971 0.029000000000000026 0.908 0.989 -31.93833221842974 large
246 prop clip_lgbm_calib_0.01 70.975 0.999 0.0010000000000000009 0.992 1.0 -952.9201057673821 large
247 prop clip_xgboost_flaml_calib_0.01 69.30178571428571 0.9985 0.0014999999999999458 0.971 1.0 -634.9621125183626 large
248 prop clip_lgbm_0.001 68.72142857142858 0.99275 0.007249999999999979 0.78 1.0 -130.61495081296087 large
249 prop clip_xgboost_calib_0.01 68.66428571428571 0.9995 0.0004999999999999449 0.947 1.0 -1906.7940855147233 large
250 prop clip_lgbm_0.0005 66.82321428571429 0.9910000000000001 0.008999999999999897 0.8315 1.0 -105.0321237699352 large
251 prop clip_lgbm_0.0001 66.72678571428571 0.984 0.016000000000000014 0.913 1.0 -58.663249754448444 large
252 prop clip_decision_tree_tuned_0.005 64.05714285714286 0.985 0.015000000000000013 0.9425 0.997 -62.63772467006149 large
253 prop clip_rf_sklearn_calib_0.005 63.69642857142857 1.0 0.0 0.984 1.0 -inf large
254 prop clip_lgbm_flaml_calib_0.005 60.95178571428571 0.9995 0.0004999999999999449 0.9965 1.0 -1906.7940855147233 large
255 prop clip_rf_flaml_calib_0.005 58.39821428571429 1.0 0.0 0.9925 1.0 -inf large
256 prop clip_decision_tree_tuned_0.0001 58.06785714285714 0.9904999999999999 0.009500000000000064 0.972 0.999 -99.45391336205537 large
257 prop clip_decision_tree_tuned_0.001 57.80535714285714 0.991 0.009000000000000008 0.9725 0.999 -105.03212376993392 large
258 prop clip_decision_tree_tuned_0.0005 57.425 0.991 0.009000000000000008 0.9725 0.999 -105.03212376993392 large
259 prop clip_lgbm_calib_0.005 55.52321428571429 1.0 0.0 0.9985 1.0 -inf large
260 prop clip_xgboost_flaml_calib_0.005 50.00535714285714 1.0 0.0 0.999 1.0 -inf large
261 prop clip_xgboost_calib_0.005 49.33571428571429 1.0 0.0 0.9995 1.0 -inf large
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