Please wait a minute...
吉林化工学院学报, 2023, 40(1): 23-28     https://doi.org/10.16039/j.cnki.cn22-1249.2023.01.006
  本期目录 | 过刊浏览 | 高级检索 |
基于Lasso特征选择乳腺癌二分类算法研究
冯欣1,张航2 **,辛瑞昊2*
1. 吉林化工学院 理学院,吉林 吉林 132022; 2. 吉林化工学院 信息与控制工程学院,吉林 吉林 132022
A Study on the Lasso Feature-based Selection Algorithm for Breast Cancer Binary Classification
FENG Xin 1, ZHANG Hang 2**, XIN Ruihao 2*
下载:  PDF (1294KB) 
输出:  BibTeX | EndNote (RIS)      
摘要 

近年来,随着大数据挖掘技术在医疗行业的迅速发展,临床精准治疗成为医疗大数据领域的研究热点。基于UCI数据库中乳腺癌数据集,通过构建乳腺癌二分类算法来预测乳腺肿瘤类型。其中针对不平衡数据集的处理、特征选择算法的优化以及分类准确率的评估,使用了机器学习技术包括随机过采样算法、Least absolute shrinkage and selection operator(Lasso)回归进行特征选择、序列前向选择(SFS)的特征选择算法。结果表明包含其中的6个特征的随机森林算法分类准确率最高(97.07%),相对于未进行特征选择算法的准确率有所提高,有可能在乳腺癌检测方面提供新的思路。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
冯欣
张航
辛瑞昊
关键词:  乳腺癌  Lasso  SFS     
Abstract: 

In recent years, with the rapid development of big data mining technology in the medical industry, clinical precision therapy has become a research hotspot in the field of medical big data. In this study, based on the breast cancer dataset in the UCI database, a breast cancer dichotomous classification algorithm was constructed to predict breast tumour types. Among them, machine learning techniques including random oversampling algorithm, Least absolute shrinkage and selection operator (Lasso) regression for feature selection, and sequential forward selection (SFS) for feature selection algorithm were used for the processing of imbalanced dataset, optimisation of feature selection algorithm and evaluation of classification accuracy. The results showed that the random forest algorithm containing six of these features had the highest classification accuracy (97.07%), which improved the accuracy relative to the algorithm without feature selection and could potentially provide new ideas in breast cancer detection.

Key words:  breast cancer    lasso    SFS
               出版日期:  2023-01-25      发布日期:  2023-01-25      整期出版日期:  2023-01-25
TP181  
引用本文:    
冯欣, 张航 , 辛瑞昊. 基于Lasso特征选择乳腺癌二分类算法研究 [J]. 吉林化工学院学报, 2023, 40(1): 23-28.
FENG Xin , ZHANG Hang , XIN Ruihao . A Study on the Lasso Feature-based Selection Algorithm for Breast Cancer Binary Classification . Journal of Jilin Institute of Chemical Technology, 2023, 40(1): 23-28.
链接本文:  
https://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2023.01.006  或          https://xuebao.jlict.edu.cn/CN/Y2023/V40/I1/23
[1] 张亚萍 , 范晓东, 张冉, 张志方. 基于SEER数据库分析辅助放疗对乳腺原发性鳞状细胞癌的生存影响 [J]. 吉林化工学院学报, 2023, 40(1): 63-67.
[1] . [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 0 .
[2] . [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 0 .
[3] SHAO Bao-li, LU Da, ZHAO Dong-hui. The Application of Dimensional Analysis in the Physical Quantity Conversion between Physical System and Numerical System [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 1 -3 .
[4] ZHANG Jian, ZHAO Xiang, QU Bo, WU Qi, LIU Yu-tong, LI Yu-shi, LIU Qun. Application of Phosphorus-sulfur-nitrogen Composite Flame Retardant in Cotton Fabric [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 4 -7 .
[5] WU Ping, REN Hong, LU Fei, WEI Qingling. A Functional Material on Recognition of Zn(II) ions based on the New Azo Compound [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 8 -10 .
[6] YANG Yan-jun, WANG Ya-hong, Yang Xiu-dong. Process Aptimization of Surfactant Assisted Extraction of Total Polyphenols from Kyllinga Brevifolia Rottb [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 11 -15 .
[7] LIU Jin-lu, LEI Yong-ping, WANG xiao-lin, ZHONG fang-li. Study on the  Purification Method of Total Saponins fromFruit of Rosa Davuvrica Pall. and its  Purification Method [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 16 -23 .
[8] SONG Jian-gang, ZHONG Fang-li, WANG Xiao-lin, LIN Yu. Study on Extraction of Anthocyanin from Aronia melanocarpa Fruit by Ionic liquid Ultrasound Assisted [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 24 -31 .
[9] TAN Li-hui, TAN Hong-wu. The Crashworthiness Analysis of different Cross-Section Thin-Walled Components [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 32 -35 .
[10] YU Wen-xin, ZHENG Kai, WANG Li-hui, LIU Hai-bo, Wang Jian-xin. The Influence of Magnetostrictive Transducer Radiation Plate material on Radiation Sound Field Distribution [J]. Journal of Jilin Institute of Chemical Technology, 2018, 35(9): 36 -40 .
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed