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Gajendra Sharma

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Open access Aug 2026

Machine Learning-Based Malware Detection: A Comparative Study of Random Forest, Decision Tree, KNN, and Linear SVM

Random Forest achieves the highest performance with a test accuracy of 96.3%, F1-score of 0.947, and AUC of 0.993, establishing it as the optimal algorithm for static malware detection tasks and establishing it as the optimal algorithm for static malware detection tasks.

Umesh Balami, Ganesh Gautam, Gajendra Sharma · 0 citations