Affiliation:
1. Bharatesh College of Computer Applications, Belagavi, Karnataka, India
Abstract
Breast cancer represents one of the dangerous diseases that causes a high number of deaths every year. The dataset containing the features present in the CSV format is used to identify whether the digitalized image is benign or malignant. The machine learning models such as Linear Regression, Decision Tree, Radom Forest are trained with the training dataset and used to classify. The accuracy of these classifiers is compared to get the best model. This will help the doctors to give proper treatment at the initial stage and save their lives.
Reference8 articles.
1. A. Bharat, N. Pooja and R. A. Reddy, "Using Machine Learning algorithms for breast cancer risk prediction and diagnosis," 2018 3rd International Conference on Circuits, Control, Communication and Computing (I4C), Bangalore, India, 2018, pp. 1-4, doi: 10.1109/CIMCA.2018.8739696.
2. B. M. Gayathri and C. P. Sumathi, "Comparative study of relevance vector machine with various machine learning techniques used for detecting breast cancer," 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Chennai, 2016, pp. 1-5, doi: 10.1109/ICCIC.2016.7919576.
3. S. Sharma, A. Aggarwal and T. Choudhury, "Breast Cancer Detection Using Machine Learning Algorithms," 2018 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS), Belgaum, India, 2018, pp. 114-118, doi: 10.1109/CTEMS.2018.8769187.
4. D. Wang and L. Jiang, "An Improved Attribute Selection Measure for Decision Tree Induction," Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), Haikou, 2007, pp. 654-658, doi: 10.1109/FSKD.2007.161.
5. Vrushali Y Kulkarni, Pradeep K Sinha, “Efficient Learning of Random Forest Classifier using Disjoint Partitioning Approach” Proceedings of the World Congress on Engineering 2013 Vol II, WCE 2013, July 3 - 5, 2013, London, U.K. ISBN: 978-988-19252-8-2 ISSN: 2078-0958 (Print); ISSN: 2078-0966 (Online).
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Breast Cancer Detection with Machine Learning-A Review;2023 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS);2023-03-23