A data scientist is evaluating a regression model and finds a high R² value but also a high RMSE. What is the most likely explanation?

AThe model is underfitting the training data

BThe target variable has high variance, so even a model that explains most of it has large absolute errors

CThe RMSE calculation has a bug; high R² always implies low RMSE

DThe model is overfitting; high RMSE is a sign of overfitting

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