Chronic-Kidney-disease-classification

Developed a system for early-stage chronic kidney disease ( CKD ) detection. • Utilized data pre-processing techniques and multiple classification models ( KNN, Decision tree, Random forest, AdaBoost, GradientBoost, Xgboost, Catboost, ExtraTree, lightgbm ) for CKD classification. • Optimized models through hyperparameter tuning using GridSearchCV . • Decision Tree model emerged as the top performer with 99% accuracy for both test and training datasets and a recall value of 96%.