Performance Analysis of XGBoost Ensemble Methods for Survivability with the Classification of Breast Cancer
Breast cancer (BC) disease is the most common and rapidly spreading disease across the globe. This disease can be prevented if identified early, and this eventually reduces the death rate. Machine learning (ML) is the most frequently utilized technology in research. Cancer patients can benefit from...
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Published in | Journal of sensors Vol. 2022; pp. 1 - 8 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Hindawi
13.09.2022
Hindawi Limited |
Subjects | |
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Abstract | Breast cancer (BC) disease is the most common and rapidly spreading disease across the globe. This disease can be prevented if identified early, and this eventually reduces the death rate. Machine learning (ML) is the most frequently utilized technology in research. Cancer patients can benefit from early detection and diagnosis. Using machine learning approaches, this research proposes an improved way of detecting breast cancer. To deal with the problem of imbalanced data in the class and noise, the Synthetic Minority Oversampling Technique (SMOTE) has been used. There are two steps in the suggested task. In the first phase, SMOTE is utilized to decrease the influence of imbalance data issues, and subsequently, in the next phase, data is classified using the Naive Bayes classifier, decision trees classifier, Random Forest, and their ensembles. According to the experimental analysis, the XGBoost-Random Forest ensemble classifier outperforms with 98.20% accuracy in the early detection of breast cancer. |
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AbstractList | Breast cancer (BC) disease is the most common and rapidly spreading disease across the globe. This disease can be prevented if identified early, and this eventually reduces the death rate. Machine learning (ML) is the most frequently utilized technology in research. Cancer patients can benefit from early detection and diagnosis. Using machine learning approaches, this research proposes an improved way of detecting breast cancer. To deal with the problem of imbalanced data in the class and noise, the Synthetic Minority Oversampling Technique (SMOTE) has been used. There are two steps in the suggested task. In the first phase, SMOTE is utilized to decrease the influence of imbalance data issues, and subsequently, in the next phase, data is classified using the Naive Bayes classifier, decision trees classifier, Random Forest, and their ensembles. According to the experimental analysis, the XGBoost-Random Forest ensemble classifier outperforms with 98.20% accuracy in the early detection of breast cancer. |
Author | Shashikala, H. K. Muthukumaran, V. Guluwadi, Suresh Mahesh, T. R. Swapna, B. Vinoth Kumar, V. |
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Cites_doi | 10.1016/j.procs.2016.04.224 10.13052/jwe1540-9589.21413 10.2991/ijcis.d.191114.002 10.18201/ijisae.2018648455 10.1155/2022/4451792 10.1109/C2I451079.2020.9368911 10.1109/TKDE.2019.2891622 10.1109/FABS52071.2021.9702566 10.1109/CSITSS54238.2021.9683524 10.1109/TIPTEKNO.2019.8895222 10.1109/RTEICT52294.2021.9573604 10.1016/j.eij.2018.03.002 10.1016/j.artmed.2004.07.002 10.1109/EBBT.2019.8741990 10.1016/j.patrec.2019.03.022 10.1155/2022/9005278 10.1109/ICGI.2017.31 10.1155/2021/1999284 |
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References | 22 G. Sindhu Madhuri (9) 2021 24 26 T. Chen (23) 10 M. Rathi (3) 2016; 5 11 13 14 15 16 17 19 2 M. Tahmooresi (20) 2018; 10 4 A. S. Hussein (18) 2019; 12 Breast cancer statistics (1) 5 6 7 8 V. D. Soni (25) 2020; 9 K. Shwetha (12) 2018; 6 21 |
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SubjectTerms | Accuracy Algorithms Breast cancer Classifiers Datasets Decision trees Disease Machine learning Mammography Medical diagnosis Medical research Methods Neural networks Survivability Womens health |
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Title | Performance Analysis of XGBoost Ensemble Methods for Survivability with the Classification of Breast Cancer |
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