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| license: cc-by-4.0 |
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| TITLE: "Machine Learning for Two-Sample Testing under Right-Censored Data: A Simulation Study" |
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| AUTHORS: |
| - PETR PHILONENKO, Ph.D. in Computer Science; |
| - SERGEY POSTOVALOV, D.Sc. in Computer Science. |
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| This dataset is a supplement to the github-project published in the https://github.com/pfilonenko/ML_for_TwoSampleTesting. This dataset contains following files: |
| 1) **two_sample_problem_dataset.tsv.gz** is a raw data. This file must be located in the "data/1_raw/"; |
| 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/"; |
| 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: |
| - **sample** is a sample type (train, val, test); |
| - **H0_H1** is a true hypothesis (H0 or H1); |
| - **Hi** is an alternative hypothesis (H01-H09, H11-H19 or H21-H29); |
| - **n1** is the size of sample 1; |
| - **n2** is the size of sample 2; |
| - **real_perc1** is an actual censoring rate of sample 1; |
| - **real_perc2** is an actual censoring rate of sample 2; |
| - **perc** is the set censoring rate for the samples 1 and 2; |
| - |
| - **Peto_test**, **Gehan_test**, **logrank_test**, **CoxMantel_test**, **BN_GPH_test**, **BN_MCE_test**, **BN_SCE_test**, **Q_test**, **MAX_Value_test**, **MIN3_test**, **WLg_logrank_test**, **WLg_TaroneWare_test**, **WLg_Breslow_test**, **WLg_PetoPrentice_test**, **WLg_Prentice_test**, **WKM_test** are test statistics of classical two-sample tests under right-censored data; |
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| Test statistics of the proposed ML-based methods: |
| - **CatBoost_test** |
| - **XGBoost_test** |
| - **LightAutoML_test** |
| - **SKLEARN_RF_test** |
| - **SKLEARN_LogReg_test** |
| - **SKLEARN_GB_test** |
