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Breast Cancer Prediction Using Dominance-based Feature Filtering Approach: A Comparative Investigation in Machine Learning Archetype
Provedor de dados: 52
Autores: Atrey,Kushangi; Sharma,Yogesh; Bodhey,Narendra K.; Singh,Bikesh Kumar.
Abstract Breast cancer is the most commonly witnessed cancer amongst women around the world. Computer aided diagnosis (CAD) have been playing a significant role in early detection of breast tumors hence to curb the overall mortality rate. This work presents an enhanced empirical study of impact of dominance-based filtering approach on performances of various state-of-the-art classifiers. The feature dominance level is proportional to the difference in means of benign and malignant tumors. The experiments were done on original Wisconsin Breast Cancer Dataset (WBCD) with total nine features. It is found that the classifiers’ performances for top 4 and top 5 dominant-based features are almost equivalent to performances for all nine features. Artificial neural...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Breast cancer; Computer aided diagnosis; Dominance-based filtering; Machine learning.
Ano: 2019
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132019000100611