Classification data to predict whether or not a person is a liver patient.
Obtained using the mlr3oml package. Contains 538 observations and 10
features. Target column is "diseased".
Pre-processing
All variables have been renamed.
The target variable has been re-encoded to
"yes"and"no".
Examples
data("ilpd", package = "mlr3data")
str(ilpd)
#> 'data.frame': 583 obs. of 11 variables:
#> $ age : int 65 62 62 58 72 46 26 29 17 55 ...
#> $ gender : Factor w/ 2 levels "Female","Male": 1 2 2 2 2 2 1 1 2 2 ...
#> $ total_bilirubin : num 0.7 10.9 7.3 1 3.9 1.8 0.9 0.9 0.9 0.7 ...
#> $ direct_bilirubin : num 0.1 5.5 4.1 0.4 2 0.7 0.2 0.3 0.3 0.2 ...
#> $ alkaline_phosphatase : int 187 699 490 182 195 208 154 202 202 290 ...
#> $ alanine_transaminase : int 16 64 60 14 27 19 16 14 22 53 ...
#> $ aspartate_transaminase: int 18 100 68 20 59 14 12 11 19 58 ...
#> $ total_protein : num 6.8 7.5 7 6.8 7.3 7.6 7 6.7 7.4 6.8 ...
#> $ albumin : num 3.3 3.2 3.3 3.4 2.4 4.4 3.5 3.6 4.1 3.4 ...
#> $ albumin_globulin_ratio: num 0.9 0.74 0.89 1 0.4 1.3 1 1.1 1.2 1 ...
#> $ diseased : Factor w/ 2 levels "yes","no": 1 1 1 1 1 1 1 1 2 1 ...