Intellectual Property India Publishes Patent Application for A Machine Learning Framework For Network Fault Severity Prediction Using Ensemble Classifiers

MUMBAI, India, Aug. 24 -- Intellectual Property India has published a patent application (202621081466 A) filed by Symbiosis International Deemed University on July 01, 2026, for A Machine Learning Framework For Network Fault Severity Prediction Using Ensemble Classifiers.

Inventors include Dr. Aniket K. Shahade; and Dr. Priyanka V. Deshmukh.

The application for the patent was published on August 21, 2026, under issue no. 34/2026.

Abstract: ABSTRACT A MACHINE LEARNING FRAMEWORK FOR NETWORK FAULT SEVERITY PREDICTION USING ENSEMBLE CLASSIFIERS The present invention discloses a machine learning framework (100) for network fault severity prediction. The framework (100) comprises a preprocessing module (110) with PCA dimensionality reduction (118), a SMOTE class imbalance module (120), a multi-classifier module (130) evaluating decision tree (132), SVM (134), AdaBoost (136), random forest (138), and XGBoost (139) classifiers, a Bayesian optimization module (140) with stratified cross-validation (144), a Shapley value feature importance module (150), and a tiered deployment module (160). XGBoost achieves 0.92 F1-score with 3.2 percent false alarm rate. The framework provides deployment recommendations for core monitoring, edge computing, and customer diagnostics. [

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