When selecting a machine learning model, what factors should be considered? A) Only the accuracy of the model on the training data. B) The complexity of the model and the nature of the problem. C) The availability of computational resources only. D) Only the interpretability of the model.
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This is important but not the only factor to consider. A model that performs well on training data may not necessarily perform well on unseen data, a situation known as overfitting. B) The complexity of the model and the nature of the problem. This is a crucial Show more…
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