Improved Classification of Breast Cancer Data Using Hybrid Techniques

Breast cancer is the second leading cancer for women in developed countries including India. Many new cancer detection and treatment approaches were developed. The most effective way to reduce breast cancer deaths is detect it earlier. The frequent occurrence of breast cancer and its serious consequ...

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Bibliographic Details
Published inCardiometry no. 26; pp. 487 - 490
Main Authors Senkamalavalli, R, Balamurugan, M, Rajulu, N Sundara, Ramshankar, N
Format Journal Article
LanguageEnglish
Published Moscow Russian New University 01.03.2023
Subjects
Accuracy
Algorithms
Breast cancer
Classification
Computer science
Data mining
Datasets
Engineering
Support vector machines
Tumors
Online AccessGet full text
ISSN2304-7232
2304-7232
DOI10.18137/cardiometry.2023.26.487490

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Summary:Breast cancer is the second leading cancer for women in developed countries including India. Many new cancer detection and treatment approaches were developed. The most effective way to reduce breast cancer deaths is detect it earlier. The frequent occurrence of breast cancer and its serious consequences have attracted world wide attention in recent years. Problems such as low rate of accuracy and poor self-adaptability still exist in traditional diagnosis. In order to solve these problems, an Ada Boost-SVM classification algorithm, Combined with к-means is proposed in this research for the early diagnosis of breast cancer. The effectiveness of the proposed methods are examined by calculating its accuracy, confusion matrix which give important clues to the physicians for early diagnosis of breast cancer.
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ISSN:2304-7232
2304-7232
DOI:10.18137/cardiometry.2023.26.487490