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".

Source

https://www.openml.org/d/1480

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 ...