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l-magnificence / Mime

Machine learning-based integration model with elegant performance
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An error occurred while running the data：The AUC score for each model was not calculated #35

Open 123wanguang123456 opened 1 month ago

123wanguang123456 commented 1 month ago

auc_dis_all(all.auc.1y,

  • dataset = names(list_train_vali_Data),
  • validate_set=names(list_train_vali_Data)[-1],
  • order= names(list_train_vali_Data),
  • width = 0.35,
  • year=1) Warning messages: 1: Removed 234 rows containing missing values or values outside the scale range (geom_text()). 2: Removed 117 rows containing missing values or values outside the scale range (geom_bar()). 3: Removed 117 rows containing missing values or values outside the scale range (geom_text()). 4: Removed 117 rows containing missing values or values outside the scale range (geom_bar()). 5: Removed 117 rows containing missing values or values outside the scale range (geom_text()). mydata: dim(list_train_vali_Data$train) [1] 364 56699 dim(list_train_vali_Data$test) [1] 156 56699 list_train_vali_Data$train[1:4,1:5] ID OS.time OS X5_8S_rRNA X5S_rRNA V1 TCGA.55.A4DF 32432 1 0 0.000000 V2 TCGA.95.8039 26317 0 0 1.000000 V3 TCGA.62.A471 23689 0 0 0.000000 V4 TCGA.49.AARR 24942 0 0 1.584963 list_train_vali_Data$test[1:4,1:5] ID OS.time OS X5_8S_rRNA X5S_rRNA V1 TCGA.35.5375 22628 0 0 1 V2 TCGA.MP.A4T4 25052 1 0 1 V3 TCGA.L9.A5IP 14681 1 0 0 V4 TCGA.50.5936 21238 1 0 0
l-magnificence commented 1 month ago

What's the result of all.auc.1y?

123wanguang123456 commented 1 month ago

@l-magnificence

This is the result of all.auc.1y.

1721210867398

This is the result of all.auc.1y scores.

[ reached 'max' / getOption("max.print") -- omitted 80 rows ]

$SuperPC$test TP FP AUC HR 1 1 1.000 NaN 1.105842 2 NaN 0.994 NaN 1.105842 3 NaN 0.987 NaN 1.105842 4 NaN 0.981 NaN 1.105842 5 NaN 0.974 NaN 1.105842 6 NaN 0.968 NaN 1.105842 7 NaN 0.962 NaN 1.105842 8 NaN 0.955 NaN 1.105842 9 NaN 0.949 NaN 1.105842 10 NaN 0.942 NaN 1.105842 11 NaN 0.936 NaN 1.105842 12 NaN 0.929 NaN 1.105842 13 NaN 0.923 NaN 1.105842 14 NaN 0.917 NaN 1.105842 15 NaN 0.910 NaN 1.105842 16 NaN 0.904 NaN 1.105842 17 NaN 0.897 NaN 1.105842 18 NaN 0.891 NaN 1.105842 19 NaN 0.885 NaN 1.105842 20 NaN 0.878 NaN 1.105842 21 NaN 0.872 NaN 1.105842 22 NaN 0.865 NaN 1.105842 23 NaN 0.859 NaN 1.105842 24 NaN 0.846 NaN 1.105842 25 NaN 0.840 NaN 1.105842 26 NaN 0.833 NaN 1.105842 27 NaN 0.827 NaN 1.105842 28 NaN 0.821 NaN 1.105842 29 NaN 0.814 NaN 1.105842 30 NaN 0.808 NaN 1.105842 31 NaN 0.801 NaN 1.105842 32 NaN 0.795 NaN 1.105842 33 NaN 0.788 NaN 1.105842 34 NaN 0.782 NaN 1.105842 35 NaN 0.776 NaN 1.105842 36 NaN 0.769 NaN 1.105842 37 NaN 0.763 NaN 1.105842 38 NaN 0.756 NaN 1.105842 39 NaN 0.750 NaN 1.105842 40 NaN 0.744 NaN 1.105842 41 NaN 0.737 NaN 1.105842 42 NaN 0.731 NaN 1.105842 43 NaN 0.724 NaN 1.105842 44 NaN 0.718 NaN 1.105842

l-magnificence commented 1 month ago

You should check the process of cal_AUC_ml_res. Maybe there are some errors.