Datasets:

Modalities:
Tabular
Text
Formats:
csv
ArXiv:
DOI:
Libraries:
Datasets
pandas
License:
pfilonenko commited on
Commit
6d7efdb
·
verified ·
1 Parent(s): 601afac

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +33 -9
README.md CHANGED
@@ -14,7 +14,7 @@ This dataset contains the synthetic data simulated by the Monte Carlo method and
14
 
15
  # Repository
16
 
17
- This dataset has following structure:
18
  ~~~
19
  data
20
  ├── 1_raw
@@ -32,13 +32,37 @@ data
32
 
33
  # Dataset & Samples
34
  In these files there are following fields:
35
- - **sample** is a sample type (train, val, test);
36
- - **H0_H1** is a true hypothesis (H0 or H1);
37
- - **Hi** is an alternative hypothesis (H01-H09, H11-H19, or H21-H29);
38
- - **n1** is the size of sample 1;
39
- - **n2** is the size of sample 2;
 
40
  - **real_perc1** is an actual censoring rate of sample 1;
41
  - **real_perc2** is an actual censoring rate of sample 2;
42
- - **perc** is the set censoring rate for the samples 1 and 2;
43
- - **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;
44
- - **CatBoost_test**, **XGBoost_test**, **LightAutoML_test**, **SKLEARN_RF_test**, **SKLEARN_LogReg_test**, **SKLEARN_GB_test** are test statistics of the proposed ML-based methods.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
14
 
15
  # Repository
16
 
17
+ The files of this dataset has following structure:
18
  ~~~
19
  data
20
  ├── 1_raw
 
32
 
33
  # Dataset & Samples
34
  In these files there are following fields:
35
+ - **sample** is a type the sample for machine learning process (train, val, test);
36
+ - **H0_H1** is a true hypothesis: **H0** when test statistics simulated have S1(t)=S2(t) and **H1** when test statistics simulated have S1(t)≠S2(t);
37
+ - **Hi** is an alternative hypothesis (H01-H09, H11-H19, or H21-H29). Detailed description of these alternatives can be find in the paper;
38
+ - **n1** is the size of the sample 1;
39
+ - **n2** is the size of the sample 2;
40
+ - **perc** is a set (expected) censoring rate for the samples 1 and 2;
41
  - **real_perc1** is an actual censoring rate of sample 1;
42
  - **real_perc2** is an actual censoring rate of sample 2;
43
+ - **Peto_test**,
44
+ - **Gehan_test**,
45
+ - **logrank_test**,
46
+ - **CoxMantel_test**,
47
+ - **BN_GPH_test**,
48
+ - **BN_MCE_test**,
49
+ - **BN_SCE_test**,
50
+ - **Q_test**,
51
+ - **MAX_Value_test**,
52
+ - **MIN3_test**,
53
+ - **WLg_logrank_test**,
54
+ - **WLg_TaroneWare_test**,
55
+ - **WLg_Breslow_test**,
56
+ - **WLg_PetoPrentice_test**,
57
+ - **WLg_Prentice_test**,
58
+ - **WKM_test** are test statistics of classical two-sample tests under right-censored data;
59
+ - **CatBoost_test**,
60
+ - **XGBoost_test**,
61
+ - **LightAutoML_test**,
62
+ - **SKLEARN_RF_test**,
63
+ - **SKLEARN_LogReg_test**,
64
+ - **SKLEARN_GB_test** are test statistics of the proposed ML-based methods.
65
+
66
+
67
+
68
+