Breast Cancer Classification using LGBM and SVM

Denesh Das; Md Masum Billah; Amit Deb Nath; Numair Bin Sharif; Kallol Kanti Mondal

doi:10.30574/ijsra.2022.7.2.0313

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Breast Cancer Classification using LGBM and SVM

Denesh Das ^{1, *}, Md Masum Billah ², Amit Deb Nath ³, Numair Bin Sharif ⁴ and Kallol Kanti Mondal⁵

1 Department of Electrical and Electronic Engineering, Southern University Bangladesh, Chattogram, Bangladesh.
2 Department of Electrical and Electronic Engineering, University of Rajshahi, Rajshahi, Bangladesh.
3 Department of Electrical and Electronic Engineering, Leading University, Sylhet, Bangladesh.
4 Department of CSE, United International University, Dhaka, Bangladesh.
5 Institute of Biological Sciences, University of Rajshahi, Rajshahi, Bangladesh.

Research Article

International Journal of Science and Research Archive, 2022, 07(02), 876-881.
Article DOI: 10.30574/ijsra.2022.7.2.0313
DOI url: https://doi.org/10.30574/ijsra.2022.7.2.0313

Publication history

Received on 07 November 2022; revised on 19 November 2022; accepted on 28 November 2022

Abstract

Breast cancer (BC) is among the most common cancers affecting women worldwide, highlighting the urgent need for early and accurate diagnosis. It develops in the breast tissue and is one of the most frequent causes of women’s death. This cancer can be cured if it is diagnosed at preliminary stage. Malignant and benign are two types of tumor found in case of breast cancer. Malignant tumors are deadly as their rate of growth is much higher than benign tumors. So, early identification of tumor type is pivotal for the appropriate treatment of a patient having breast cancer. Machine learning (ML) has emerged as a powerful tool for BC classification, enhancing diagnostic precision and improving patient outcomes. In this work, Wisconsin Breast Cancer Dataset is used. Our goal is to analyze the dataset and evaluate the performance of LGBM and SVM for predicting breast cancer.

Keywords

Breast Cancer Diagnosis; WBCD Dataset; Malignant; Benign; Classification; Machine Learning; LGBM; SVM

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How to cite this article

Denesh Das, Md Masum Billah, Amit Deb Nath, Numair Bin Sharif and Kallol Kanti Mondal. Breast Cancer Classification using LGBM and SVM. International Journal of Science and Research Archive, 2022, 07(02), 876-881. Article DOI: https://doi.org/10.30574/ijsra.2022.7.2.0313

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