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Update results from script: scripts/irm/lpq_coverage.py
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‎results/irm/lpq_coverage_lpq0.csv

Lines changed: 8 additions & 8 deletions
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Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
2-
LGBM,LGBM,0.9,0.94,1.1717023704378204,0.23177376824257415,100
3-
LGBM,LGBM,0.95,0.9722222222222223,1.396169488293374,0.23177376824257415,100
4-
LGBM,Logistic Regression,0.9,0.95,1.1248327860637255,0.2271354130168218,100
5-
LGBM,Logistic Regression,0.95,0.9755555555555556,1.3403209338454969,0.2271354130168218,100
6-
Logistic Regression,LGBM,0.9,0.95,1.1516756381210271,0.22092321662449366,100
7-
Logistic Regression,LGBM,0.95,0.9811111111111112,1.372306164879188,0.22092321662449366,100
8-
Logistic Regression,Logistic Regression,0.9,0.9533333333333333,1.1095156391492578,0.20615547550299898,100
9-
Logistic Regression,Logistic Regression,0.95,0.9788888888888888,1.3220694275677582,0.20615547550299898,100
2+
LGBM,LGBM,0.9,0.94,1.1717023704378204,0.23180102735661154,100
3+
LGBM,LGBM,0.95,0.9722222222222223,1.396169488293374,0.23180102735661154,100
4+
LGBM,Logistic Regression,0.9,0.95,1.1248311184133066,0.2270596212748565,100
5+
LGBM,Logistic Regression,0.95,0.9755555555555556,1.3403189467174592,0.2270596212748565,100
6+
Logistic Regression,LGBM,0.9,0.9488888888888889,1.1516756381210271,0.22097455311738945,100
7+
Logistic Regression,LGBM,0.95,0.9811111111111112,1.372306164879188,0.22097455311738945,100
8+
Logistic Regression,Logistic Regression,0.9,0.9533333333333333,1.1095156391492575,0.20619468880954653,100
9+
Logistic Regression,Logistic Regression,0.95,0.9788888888888888,1.3220694275677582,0.20619468880954653,100

‎results/irm/lpq_coverage_lpq1.csv

Lines changed: 8 additions & 8 deletions
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Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
2-
LGBM,LGBM,0.9,0.9577777777777777,1.6624989751251327,0.32781267630898475,100
3-
LGBM,LGBM,0.95,0.99,1.9809897137285786,0.32781267630898475,100
4-
LGBM,Logistic Regression,0.9,0.9411111111111111,1.5914676830888603,0.32199246221295674,100
5-
LGBM,Logistic Regression,0.95,0.97,1.8963507088437095,0.32199246221295674,100
6-
Logistic Regression,LGBM,0.9,0.96,1.60784858202307,0.30086810092875493,100
7-
Logistic Regression,LGBM,0.95,0.9822222222222223,1.915869753833108,0.30086810092875493,100
8-
Logistic Regression,Logistic Regression,0.9,0.9477777777777777,1.5561898364166578,0.30507352946060423,100
9-
Logistic Regression,Logistic Regression,0.95,0.9844444444444445,1.854314561798947,0.30507352946060423,100
2+
LGBM,LGBM,0.9,0.9577777777777777,1.6624989751251327,0.3276833414641952,100
3+
LGBM,LGBM,0.95,0.99,1.9809897137285786,0.3276833414641952,100
4+
LGBM,Logistic Regression,0.9,0.9411111111111111,1.5914659538910119,0.32194623632362507,100
5+
LGBM,Logistic Regression,0.95,0.9711111111111111,1.8963486483773861,0.32194623632362507,100
6+
Logistic Regression,LGBM,0.9,0.96,1.60784858202307,0.30083496643464896,100
7+
Logistic Regression,LGBM,0.95,0.9822222222222223,1.915869753833108,0.30083496643464896,100
8+
Logistic Regression,Logistic Regression,0.9,0.9466666666666668,1.556189836416658,0.304958909712274,100
9+
Logistic Regression,Logistic Regression,0.95,0.9844444444444445,1.8543145617989472,0.304958909712274,100

‎results/irm/lpq_coverage_lqte.csv

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Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
2-
LGBM,LGBM,0.9,0.9233333333333333,1.636872420792144,0.3849163075483558,0.94,2.2547716211801454,100
3-
LGBM,LGBM,0.95,0.9633333333333333,1.950453790824845,0.3849163075483558,0.97,2.5400452907969764,100
4-
LGBM,Logistic Regression,0.9,0.9077777777777777,1.5675486277219108,0.3750309062078869,0.91,2.157430608143212,100
5-
LGBM,Logistic Regression,0.95,0.95,1.8678493964501393,0.3750309062078869,0.95,2.4273382603132627,100
6-
Logistic Regression,LGBM,0.9,0.9188888888888889,1.6190226009242576,0.3723079594843724,0.92,2.208051172256097,100
7-
Logistic Regression,LGBM,0.95,0.9644444444444444,1.9291844185850642,0.3723079594843724,0.98,2.4873844228896727,100
8-
Logistic Regression,Logistic Regression,0.9,0.9077777777777777,1.564249778556274,0.37200263232334746,0.9,2.1368366984439215,100
9-
Logistic Regression,Logistic Regression,0.95,0.9477777777777777,1.8639185752213465,0.37200263232334746,0.95,2.4083334749081065,100
2+
LGBM,LGBM,0.9,0.9233333333333333,1.636872420792144,0.38490701730912247,0.94,2.2547716211801454,100
3+
LGBM,LGBM,0.95,0.9622222222222223,1.950453790824845,0.38490701730912247,0.97,2.5400452907969764,100
4+
LGBM,Logistic Regression,0.9,0.9088888888888889,1.5675334432220174,0.37520599979698516,0.91,2.1574364137437168,100
5+
LGBM,Logistic Regression,0.95,0.95,1.8678313030025362,0.37520599979698516,0.95,2.4273297337432616,100
6+
Logistic Regression,LGBM,0.9,0.9188888888888889,1.6190226009242576,0.3723322348549169,0.92,2.208051172256097,100
7+
Logistic Regression,LGBM,0.95,0.9644444444444444,1.9291844185850637,0.3723322348549169,0.98,2.487384422889672,100
8+
Logistic Regression,Logistic Regression,0.9,0.9066666666666667,1.5642497785562741,0.3720685867269132,0.9,2.1368366984439215,100
9+
Logistic Regression,Logistic Regression,0.95,0.9477777777777777,1.8639185752213465,0.3720685867269132,0.95,2.4083334749081065,100

‎results/irm/lpq_coverage_metadata.csv

Lines changed: 1 addition & 1 deletion
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DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
2-
0.10.dev0,lpq_coverage.py,2025-01-08 17:24:33,18545.282371282578,3.12.8
2+
0.10.dev0,lpq_coverage.py,2025-05-22 16:36:53,18251.836868286133,3.12.10

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