Publication Date: 2022/06/28
Abstract: Breast cancer causes more death in women and it also curable if it is early diagnosed. Hence, early detection of cancer in women will be helpful in taking necessary actions. In order to detect the disease supervised machine learning techniques is discussed in this paper. With the help of Sequential ForwardSelection (SFS) best feature will be selected for support vector machines (SVM) model. Wisconsin breast cancerdataset (WBCD) is used for diagnosis of breast cancer. The SVM result shows 96% precision because of random permutation on the data set.
Keywords: Sequential Forward Selection SFS; Support Vector Machine; Breast Cancer; Classification; Machine Learning; Wisconsin Breast Cancer Dataset.
DOI: https://doi.org/10.5281/zenodo.6767080
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT22JUN490.pdf
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