Is noise always bad?
Noise is not always bad/worse since it represents unpredictability in the real world scenarios. On the other hand, too much noise might confuse important patterns and reduce model performance. Noise can sometimes add diversity, which improves the robustness and generalization of the model. In order to handle noise properly, one must weigh its effects against the requirement for model accuracy. Noise impacts can be made better with the use of proper , implementation of strategies like regularization. For the purpose of maximizing model performance in practical scenarios, it is imperative to comprehend the nature and origin of noise.
How to handle Noise in Machine learning?
Random or irrelevant data that intervene in learning’s is termed as noise.