Table 3 Features description
From: Chronic kidney disease prediction using machine learning techniques
Symbols | Features full name | Type | Class | Missing values in % |
|---|---|---|---|---|
Age | Age | Numeric | Predictor | 0 |
Gender | Gender | Nominal | Predictor | 0 |
Bp | Blood pressure | Numeric | Predictor | 0.058207 |
Sg | Specific gravity | Nominal | Predictor | 0.058207 |
Chl | Chloride | Numeric | Predictor | 0.116414 |
Sod | Sodium | Numeric | Predictor | 0.232829 |
Pot | Potassium | Numeric | Predictor | 0.116414 |
Bun | Blood Urea Nitrogen | Numeric | Predictor | 0.232829 |
Scr | Serum Creatinine | Numeric | Predictor | 0.058207 |
Hgb | Hemoglobin | Numeric | Predictor | 0.232829 |
Rbcc | Red blood cell count | Numeric | Predictor | 0.232829 |
Wbcc | White blood cell count | Numeric | Predictor | 0.232829 |
Mcv | Mean cell volume | Numeric | Predictor | 6.111758 |
Pltc | Platelet count | Numeric | Predictor | 7.275902 |
Htn | Hypertension | Nominal | Predictor | 0 |
Dm | Diabetes Mellitus | Nominal | Predictor | 0 |
Ane | Anemia | Nominal | Predictor | 0 |
Hd | Heart disease | Nominal | Predictor | 0 |
ckd_status | ckd_status | Nominal | Target | 0 |