2024
DOI: 10.52783/jes.2585
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Enhancing Breast Cancer Detection with Ensemble Machine Learning Models

Dawood Salim Mohammed

Abstract: Breast cancer remains a significant public health issue worldwide, underlining the need for accurate and efficient diagnostic methods. In this paper, we propose a new technique to enhance breast cancer diagnosis through the integration of multiple machine-learning models. Our strategy employs a combination of the Naive Bayes classifier, Stochastic Gradient Descent (SGD), Bagging, and the ZeroR classifier, alongside Bayes Network learning. The cornerstone of our approach is Bayes Network learning, a probabilist… Show more

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