Breast Tumor Classification Diagnosis Based on LS-SVM

Chao Liu, Bo Zhou, Qingzhu Li, Yu Chen, Guowei Qin, Guangkuo Hu

2018

Abstract

To accurately predict breast cancer, breast cancer prediction method based on least squares support vector (LS-SVM) proposed. Patients with breast cancer through the data on the basis of 469 cases, including 400 cases of data relevance vector machine training, and the remaining 69 cases data sample tests, and finally through with neural networks, support vector machines comparison, breast cancer diagnosis model based on LS-SVM prediction accuracy is higher than the neural network and support vector machine. Has good diagnostic value of breast cancer diagnosis based on LS-SVM model, which provides a new method for breast cancer diagnosis.

Paper Citation

in Harvard Style

Liu C., Zhou B., Li Q., Chen Y., Qin G. and Hu G. (2018). Breast Tumor Classification Diagnosis Based on LS-SVM.In Proceedings of the 2nd International Conference on Intelligent Manufacturing and Materials - Volume 1: ICIMM, ISBN 978-989-758-345-2, pages 579-582. DOI: 10.5220/0007536105790582

in Bibtex Style

@conference{icimm18,
author={Chao Liu and Bo Zhou and Qingzhu Li and Yu Chen and Guowei Qin and Guangkuo Hu},
title={Breast Tumor Classification Diagnosis Based on LS-SVM},
booktitle={Proceedings of the 2nd International Conference on Intelligent Manufacturing and Materials - Volume 1: ICIMM,},
year={2018},
pages={579-582},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007536105790582},
isbn={978-989-758-345-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Intelligent Manufacturing and Materials - Volume 1: ICIMM,
TI - Breast Tumor Classification Diagnosis Based on LS-SVM
SN - 978-989-758-345-2
AU - Liu C.
AU - Zhou B.
AU - Li Q.
AU - Chen Y.
AU - Qin G.
AU - Hu G.
PY - 2018
SP - 579
EP - 582
DO - 10.5220/0007536105790582