Breast Cancer Prediction Using AdaBoost And XGBoost Classifier
Ankita, Sonam Mittal · 2024
Breast cancer is a very noxious cancer in women worldwide, its mortality rate is increasing day by day. Researchers found various research methods for the detection of breast cancer such as mammographic images, CT scans, etc, but these are also not well suited for early prediction of breast cancer. Machine Learning (ML) is part of Artificial intelligence (AI), which has different methods for the early prediction of any disease. To identify breast cancer before its occurrence various ML algorithms are used. In this paper, two ML classifiers are used for the classification and prediction of breast cancer, such as the AdaBoost and XGBoost classifier. These classifiers use Lasso Cross Validation (CV) for the enhancement of the accuracy. AdaBoost performed better than the XGBoost classifier because AdaBoost has the quality of handling the imbalanced data effectively.