Question: Model A is trained on a classification problem with 4 features and achieves 9 0 % accuracy on the test set. The same model is

Model A is trained on a classification problem with 4 features and achieves 90% accuracy on the test set.
The same model is trained on the same problem using only 3 of the features and achieves 50% accuracy on the test set.
What can you conclude about the feature that was left out in the second run?

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