Ensemble Learning Applied to Classification of Malignant and Benign Breast Cancer
In this study, we show how ensemble learning can be useful for the future of breast cancer diagnosis. The chosen ensemble learning method was bagging, which made use of the classifiers Support Vector Machine (SVM), Decision Tree (DT) and Naive Bayes (NB) in order to classify mammograms as benign or...
Main Authors: | Segerström, Pierre, Boltshauser, Felix |
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Format: | Others |
Language: | English |
Published: |
KTH, Skolan för elektroteknik och datavetenskap (EECS)
2021
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Subjects: | |
Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302551 |
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