“Advanced Analysis of Learning-Based Spam Email Filtering Methods Based on Feature Distribution Differences of Dataset.” has been added to your cart. View cart
Aim:
To apply various machine learning algorithms to analyze medical data and predict the likelihood of heart and liver diseases, assisting healthcare professionals in making informed decisions for diagnosis and treatment.
Ā Ā Ā Ā Ā To develop an optimized machine-learning model using Random Forest to accurately classify brain stroke risk using clinical, demographic, and physiological data.
Ā Ā Ā Ā Ā Ā Ā Design and deliver a lightweight, adaptive, and high-generalization intrusion detection framework that accurately identifies zero-day and known cyberattacks in network traffic while maintaining efficient real-time performance.
Ā Ā Ā Ā This study aims to improve the accuracy of spam email detection by leveraging the advanced contextual capabilities of the DistilBERT model for text classification.