This is a Machine Learning project using Classification Use Case
STEPS USED
- Renaming the columns heads using data description.txt
- Converting Object to Numerical Columns
- Extracting Numerical and Categorical Columns
- Checking for Dirtyness in data
- Ploting a heatmap and finding the best correlation
- Finding relationships between Data variables
- Plots- scatter, violin, kdeplot
Preform Exploratory Data Anlysis and Build a model to predict- If a preson has a chronic kidney disease or not
- Finding and filling the missing values
- Feature Encoding techniques to find the the important features
- Selecting important features
- XGB Classifier- XGBost Algorithm
- RandomizedSearchCV
- Cross validate the model and find accuracy