Aim
The aim of this project is to develop a predictive model for chronic kidney disease (CKD) based on patient data and relevant medical factors. The objective is to accurately predict the presence or absence of CKD in patients, aiding in early detection and timely intervention.
Details
- What the features will your script have
My intiution is to do first Data Preprocess and perform EDA on the kidney dataset and then do the feature encoding on the dataset which helps me to get the best features for the model. On the basis of classification or regression problem I made the best ML model for the prediction of CKD with best results and accuracy.
Summary
Project involves data preprocessing, exploratory data analysis (EDA), and feature engineering. It aims to develop an accurate predictive model by selecting the best machine learning algorithm based on the nature of the problem (classification or regression). The model's performance is optimized through hyperparameter tuning.
Aim
The aim of this project is to develop a predictive model for chronic kidney disease (CKD) based on patient data and relevant medical factors. The objective is to accurately predict the presence or absence of CKD in patients, aiding in early detection and timely intervention.
Details
My intiution is to do first Data Preprocess and perform EDA on the kidney dataset and then do the feature encoding on the dataset which helps me to get the best features for the model. On the basis of classification or regression problem I made the best ML model for the prediction of CKD with best results and accuracy.
Summary
Project involves data preprocessing, exploratory data analysis (EDA), and feature engineering. It aims to develop an accurate predictive model by selecting the best machine learning algorithm based on the nature of the problem (classification or regression). The model's performance is optimized through hyperparameter tuning.