What is overfitting in machine learning, and how can it be addressed in a pipeline?
A . Overfitting occurs when the model is too simple and underperforms.
B . Overfitting occurs when the model fits the training data too closely and may not generalize well. It can be addressed by regularization techniques.
C . Overfitting occurs when the model is too complex and overperforms.
D . Overfitting is not a concern in machine learning pipelines.
Answer: B
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