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Finding unknown stimulants applied in food Supplements using Artificial Intelligence
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Description
It is therefore of the utmost importance for the competent authorities to know when new products are being marketed and to warn users against potential health risks. In this study, an approach is presented to detect new and unknown stimulants in food supplements using machine learning. The input data is taken from the dataset repository. In our process, we are take the food supplements dataset as input. The system is developed the machine learning algorithm such as random forest and KNN. The results shows that the performances metrics such as accuracy, sensitivity and specificity. Finally, compare the two algorithms based on results in the form of graph. Finally, we can predict the food supplements is new or unknown simulants. Including Packages
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