Accuracy comparison with base classifiers and the proposed stacking model.

Accuracy comparison with base classifiers and the proposed stacking model.

<p>Accuracy comparison with base classifiers and the proposed stacking model.</p>

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Bibliographic Details
Main Author:	Ye Tian (220278) (author)
Other Authors:	Xin Dai (152712) (author), Zhijun Li (475291) (author), Hong Guo (142424) (author), Xiao Mao (10538435) (author)
Published:	2025
Subjects:	Medicine Cancer Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified strategically combines predictions modern cybersecurity infrastructure hyperparameter space optimization existing solutions documented enabling systematic identification emerging challenge underscores 79 %), precision email communication systems maximize detection performance email usage xlink "> widespread adoption valuable time user experience unsolicited messages thereby jeopardizing spam proliferation phishing schemes parameter configurations malware distribution machine learning learner integration internet technologies information overload exponential growth enhanced model empirical analysis digital security detection accuracy critical importance corresponding surge baseline models
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