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A comparative study of decision tree and support vector machine for breast cancer prediction

Fuente: Zenodo

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Détails bibliographiques
Auteurs principaux:	Matthew Idakwo Ogbe, ⁠Christian Chukwuemeka Nzeanorue, Raphael Aduramimo Olusola, Daniel Oluwafemi Olofin, Moyosore Celestina Owoeye, Ewemade Cornelius Enabulele, Adeoluwa Perpetual Ibijola, Chioma Jessica Ifechukwu, Olanipekun Ibrahim Ayo
Format:	Recurso digital
Langue:	anglais
Publié:	Zenodo 2024
Sujets:	Support Vector Machine (SVM) Breast Cancer Diagnosis Machine Learning Wisconsin Breast Cancer Dataset Classification Accuracy Data Mining
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

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