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The proposed XGBoost model was developed for heart disease risk assessment and evaluated using accuracy, precision, recall, and F1-score, demonstrating its effectiveness and reliability for accurate heart disease prediction.
A machine learning approach to build a cybersecurity threat intelligence framework for effective multiclass intrusion detection, in which the Decision Tree classifier is used, which beats state-of-the-art deep learning and ML approaches in terms of performance, execution time, and computational complexity.
Security researchers rely heavily on Network Intrusion Detection Systems (NIDS) to keep an eye on network traffic and notify administrators of any suspicious activities. The purpose of this paper is to offer a comprehensive overview of intrusion detection systems (IDS), including the following topics: fundamentals, kin...
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