Early Detection of Breast Cancer Using Machine Learning and Ensemble Techniques
Keywords:Breast cancer prediction, Ensemble Machine Learning algorithms, AdaBoost, XGBoost, F1-Score
Breast Cancer is found as the most dangerous and most commonly affecting diseases in the world by WHO. The severity of breast cancer and early diagnosis of it has gained the attention of researchers to save humankind from such devastating disease. Early prediction of breast cancer has geared up its journey after the introduction to machine learning supervised algorithms. In the paper, the use of various machine learning algorithms along with the ensemble algorithms is shown. The results obtained are highly accurate to help one correctly predict cancer. The paper aims at early diagnosis of breast cancer with a humble motto of saving patients suffering from the disease by allowing them to know whether the diagnosed tumor is cancerous or non-cancerous, being Malignant and Benign respectively. This paper would be useful and aiding for those who are novel researchers in prediction and diagnosis of breast cancer using machine learning.
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