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Research Article

EEO. 2021; 20(4): 3975-3980


Comparative Analysis Of Breast Cancer Prediction Based On Machine Learning Techniques

Prakash Srivastava, Dr. Suruchi Sharma.




Abstract

There are no typical symptoms of cancer; instead, it depends on the section of the body where the cancer has developed. Cancer is a well-known fatal disease that spreads throughout the body of the patient and is basically an uncommon, abnormal, or distinct sort of growth of tissues or cells. The goal of this endeavor is to make a contribution to the healthcare industry. It concerns the malignant or benign nature of a tumour. The report primarily focuses on the causes of breast cancer, using several machine learning algorithms that can be used for prediction, and then comparing the accuracy of each method. We utilised the most recent techniques because the earlier systems we evaluated applied fewer techniques, used an older database, and used overfitting of data so that we could compare more methods, we chose the most recent database. Our machine learning model has outperformed a number of current cutting-edge breast cancer prediction tools.

Key words: SVM, Decision Trees , Random Forest, prediction.






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The articles in Bibliomed are open access articles licensed under Creative Commons Attribution 4.0 International License (CC BY), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.