An Ensemble Learning Approach for Student Performance Analysis of a Higher Educational Institute using a SHAP-Based Feature Selection and Optuna Optimization
Forecasting and assessing student performance are crucial for allowing educators to pinpoint deficiencies and promote grade improvement. A thorough comprehension of feature contributions is crucial for improving model interpretability and facilitating informed decision-making in academic institutions. Explainable artificial intelligence encompasses methodologies and strategies designed to deliver transparent and accessible rationales for the decisions rendered by…
Read More HLLSet Theory: A Unified Framework for Probabilistic Knowledge Representation
This paper introduces HLLSet (HyperLogLog Set), a probabilistic data structure that behaves like a set under all standard operations while containing no explicit elements. Unlike traditional HyperLogLog, which only estimates cardinality, HLLSets support full set operations (union, intersection, difference) through enhanced register structures and provide a principled framework for representing semantic relationships. We establish a…
Read More Hybrid Feature Selection for Anomaly Detection in IoT Network Intrusion Detection Systems
The rapid growth of Internet of things (IoT) devices have heightened the need for effective Intrusion Detection System (IDS) to combat evolving cyber threats. The IoT networks has the security challenges due to the heterogeneous and high-dimensional nature of network traffic data, redundant features, and class imbalance which hinder detection accuracy and efficiency. Effective IDS…
Read More TL-SOC: A Hybrid Decision-Centric Intrusion Detection Framework for Security Operations Centers
Security Operations Centers (SOCs) require intrusion detection systems that achieve high detection accuracy while maintaining a low false-positive rate and robustness to evolving attack patterns. However, most existing machine learning-based approaches primarily focus on detecting known threats and often overlook distribution shifts and the reliability of generated alerts. In this paper, we propose TL-SOC, a…
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