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A medical company has decided to automate the process of cancer screening using machine learning. The Data Science team collected the company’s patients’ records over five years which consisted of 1,000 positive samples and 200,000 negative samples where positive samples indicate that the patient had cancer. A random forest model along with an XGBoost model were proposed, and the company wanted the data science team to evaluate both of them to choose the best model. What is the most suitable evaluation technique should be adopted by the team given the data imbalance?