Automated Root Cause Analysis of Network Failures in IPMPLS Network Using Machine Learning and Case-Based Reasoning

The project, Automated Root Cause Analysis of Network Failures in IPMPLS Network Using Machine Learning and Case-Based Reasoning, aims to streamline and automate the identification of root causes behind network failures in IP/MPLS environments. By leveraging machine learning models and case-based reasoning techniques, it analyzes network traffic data to detect anomalies and classify failure patterns. This helps network administrators quickly diagnose issues, reduce downtime, and improve network reliability. The web application facilitates secure user access, dataset uploads, model evaluation, and real-time prediction, ultimately enabling efficient, data-driven troubleshooting and proactive network management.