Evaluation Based Approaches For Liver Disease Prediction Using Machine Learning Algorithms

Project Synopsis & Overview

This project evaluates machine learning algorithms for predicting chronic liver disease from patient health data. It compares Logistic Regression, K-Nearest Neighbors (KNN), Decision Tree, Support Vector Machine (SVM), and Random Forest models to identify effective classification approaches. Data preprocessing, model training, performance evaluation, and graphical comparison help assess predictive results and support early risk screening and informed clinical decision-making effectively.

Complete Technical Specifications