CDC.-.Disease.Risk.mp4
Source: Centers for Disease Control more youtbe videos: NHS Imperial College Health
Task: Detect chronic kidney disease using support vector machine, the class is binary with the value (ckd,notckd). Where cdk means the presence of Chronic Kidney disease and not 'cdk' means healthy.
Dataset: UCI Machine Learning
Complete JupyterNotebook: Link
| Algorithm | Recall | Precision | F1-score | Accuracy | Jaccard Index |
|---|---|---|---|---|---|
| Support Vector Machine (linear) | 100% | 100% | 100% | 100% | 100% |
This dataset is composed of 400 instances with 25 attributes, it contains missing values as welll make almost 55%, so please make sure to use EDA before running any visualization of ML algorithm.
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 - (ckd,notckd)