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@@ -13,6 +13,7 @@ This dataset is a supplement to the github-project published in the https://gith
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  2) **sample_train.tsv.gz** and **sample_simulation.tsv.gz** are train and test samples splited from the **two_sample_problem_dataset.tsv.gz**. These files must be located in the "data/2_samples/";
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  3) **dataset_with_ML_pred.tsv.gz** is the test sample supplemented by the predictions of the proposed ML-methods. This file must be located in "data/3_dataset_with_ML_pred/".
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  - **sample** is a sample type (train, val, test);
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  - **H0_H1** is a true hypothesis (H0 or H1);
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  - **Hi** is an alternative hypothesis (H01-H09, H11-H19 or H21-H29);
@@ -21,6 +22,7 @@ This dataset is a supplement to the github-project published in the https://gith
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  - **real_perc1** is an actual censoring rate of sample 1;
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  - **real_perc2** is an actual censoring rate of sample 2;
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  - **perc** is the set censoring rate for the samples 1 and 2;
 
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  - **Peto_test**
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  - **Gehan_test**
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  - **logrank_test**
@@ -36,7 +38,8 @@ This dataset is a supplement to the github-project published in the https://gith
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  - **WLg_Breslow_test**
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  - **WLg_PetoPrentice_test**
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  - **WLg_Prentice_test**
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- - **WKM_test**
 
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  - **CatBoost_test**
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  - **XGBoost_test**
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  - **LightAutoML_test**
 
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  2) **sample_train.tsv.gz** and **sample_simulation.tsv.gz** are train and test samples splited from the **two_sample_problem_dataset.tsv.gz**. These files must be located in the "data/2_samples/";
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  3) **dataset_with_ML_pred.tsv.gz** is the test sample supplemented by the predictions of the proposed ML-methods. This file must be located in "data/3_dataset_with_ML_pred/".
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+ In these files there are following fields:
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  - **sample** is a sample type (train, val, test);
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  - **H0_H1** is a true hypothesis (H0 or H1);
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  - **Hi** is an alternative hypothesis (H01-H09, H11-H19 or H21-H29);
 
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  - **real_perc1** is an actual censoring rate of sample 1;
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  - **real_perc2** is an actual censoring rate of sample 2;
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  - **perc** is the set censoring rate for the samples 1 and 2;
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+ Values of classical two-sample tests under right-censored data:
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  - **Peto_test**
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  - **Gehan_test**
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  - **logrank_test**
 
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  - **WLg_Breslow_test**
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  - **WLg_PetoPrentice_test**
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  - **WLg_Prentice_test**
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+ - **WKM_test**
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+ Values of the proposed ML-based methods:
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  - **CatBoost_test**
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  - **XGBoost_test**
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  - **LightAutoML_test**