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Noise Addition is a technique used in various fields such as Data Analysis, Machine Learning, and Signal Processing to improve the robustness and Generalization of models by intentionally adding Random variations to the data. This process helps in preventing overfitting, Enhancing privacy, and Simulating real-world conditions where data is often imperfect.
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