/kidney-disease-prediction

Primary LanguageJupyter Notebook

Description

The data was taken over a 2-month period in India with 25 features ( eg, red blood cell count, white blood cell count, etc). The target is the 'classification', which is either 'ckd' or 'notckd' - ckd=chronic kidney disease. Uses machine learning techniques to predict if a patient is suffering from a chronic kidney disease or not.

Data Set Information:

Attribute Information

We use the following representation to collect the dataset:-

  • age - age
  • bp - blood pressure
  • sg - specific gravity
  • al - albumin
  • su - sugar
  • rbc - red blood cells
  • pc - pus cell
  • pcc - pus cell clumps
  • ba - bacteria
  • bgr - blood glucose random
  • bu - blood urea
  • sc - serum creatinine
  • sod - sodium
  • pot - potassium
  • hemo - hemoglobin
  • pcv - packed cell volume
  • wc - white blood cell count
  • rc - red blood cell count
  • htn - hypertension
  • dm - diabetes mellitus
  • cad - coronary artery disease
  • appet - appetite
  • pe - pedal edema
  • ane - anemia
  • class - class
  • Additional Feature Details
  • Attribute Information:

We use 24 + class = 25 ( 11 numeric ,14 nominal)

  • Age(numerical) - age in years
  • Blood Pressure(numerical) - bp in mm/Hg
  • Specific Gravity(nominal) - sg - (1.005,1.010,1.015,1.020,1.025)
  • Albumin(nominal) - al - (0,1,2,3,4,5)
  • Sugar(nominal) - su - (0,1,2,3,4,5)
  • Red Blood Cells(nominal) - rbc - (normal,abnormal)
  • Pus Cell (nominal) - pc - (normal,abnormal)
  • Pus Cell clumps(nominal) - pcc - (present,notpresent)
  • Bacteria(nominal) - ba - (present,notpresent)
  • Blood Glucose Random(numerical) - bgr in mgs/dl
  • Blood Urea(numerical) -bu in mgs/dl
  • Serum Creatinine(numerical) - sc in mgs/dl
  • Sodium(numerical) - sod in mEq/L
  • Potassium(numerical) - pot in mEq/L
  • Hemoglobin(numerical) - hemo in gms
  • Packed Cell Volume(numerical)
  • White Blood Cell Count(numerical) - wc in cells/cumm
  • Red Blood Cell Count(numerical) - rc in millions/cmm
  • Hypertension(nominal) - htn - (yes,no)
  • Diabetes Mellitus(nominal) - dm - (yes,no)
  • Coronary Artery Disease(nominal) - cad - (yes,no)
  • Appetite(nominal) - appet - (good,poor)
  • Pedal Edema(nominal) - pe - (yes,no)
  • Anemia(nominal) - ane - (yes,no)
  • Class (nominal)- class - (ckd,notckd)