| Summary: | Today, breast cancer is one of the most common diseases that can cause certain complications, sometimes worst-case scenario is death. Thus, there is an urgent need for a diagnosis tool that can help doctors detect the disease at an early stage and recommend the necessary lifestyle changes to stop the progression of the disease; the likelihood of developing cancer at a young age has also been greatly increased by environmental changes in our everyday lives. Machine learning is an urgent need today to enhance human effort and offer higher automation with fewer errors. In this article, a breast cancer detection and prediction system is developed based on machine learning models (SVM, NB, AdaBoost). The achieved accuracies of the developed models are as follows: SVM achieved an overall score of 98.82%, NB achieved an overall score of 97.71%, and finally, AdaBoost achieved an overall score of 97.71%.
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