Breast Cancer Classification using RBF and BPN Neural Networks

Content Provider	Semantic Scholar
Author	Vijayalakshmi, K.
Copyright Year	2017
Abstract	This paper explores the possible diagnosis of breast cancer using Radial Basis Function (RBF) for the data set. The use of machine learning and data mining techniques has revolutionized the whole process of breast cancer Diagnosis and Prognosis. Breast Cancer Diagnosis distinguishes benign from malignant breast lumps and Breast Cancer Prognosis predicts when Breast Cancer is likely to recur in patients that have had their cancers excised. We analyze the breast Cancer data available from the Wisconsin Breast Cancer WBC, WDBC from UCI machine learning with the aim of developing accurate prediction models for breast cancer using RBF. Overall, the RBF neural network technique has proved better performance than that of the BPN technique.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.ripublication.com/ijaer17/ijaerv12n15_%20(4).pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article