Detection of Malignant and Benign Breast Cancer Using the ANOVA-BOOTSTRAP-SVM

作     者：Borislava Petrova Vrigazova 

作者机构：Department of Statistics and EconometricFaculty of Economics and Business AdministrationSofia UniversityBulgaria 

出 版 物：《Journal of Data and Information Science》 (数据与情报科学学报（英文版）)

年 卷 期：2020年第5卷第2期

页      面：62-75页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 1002[医学-临床医学] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 100214[医学-肿瘤学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学] 

主　　题：Breast cancer detection ANOVA Bootstrap Support vector machines 

摘      要：Purpose:The aim of this research is to propose a modification of the ANOVA-SVM method that can increase accuracy when detecting benign and malignant breast ***:We proposed a new method *** involves applying the analysis of variance(ANOVA)to support vector machines(SVM)but we use the bootstrap instead of cross validation as a train/test splitting *** have tuned the kernel and the C parameter and tested our algorithm on a set of breast cancer ***:By using the new method proposed,we succeeded in improving accuracy ranging from 4.5 percentage points to 8 percentage points depending on the *** limitations:The algorithm is sensitive to the type of kernel and value of the optimization parameter *** implications:We believe that the ANOVA-BOOTSTRAP-SVM can be used not only to recognize the type of breast cancer but also for broader research in all types of ***/value:Our findings are important as the algorithm can detect various types of cancer with higher accuracy compared to standard versions of the Support Vector Machines.