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A data scientist has created a linear regression model that useslog(price)as a label variable.

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A data scientist has created a linear regression model that useslog(price)as a label variable. Using this model, they have performed inference and the predictions and actual label values are in Spark DataFramepreds_df.

They are using the following code block to evaluate the model:

regression_evaluator.setMetricName("rmse").evaluate(preds_df)

Which of the following changes should the data scientist make to evaluate the RMSE in a way that is comparable withprice?

A.

They should exponentiate the computed RMSE value

B.

They should take the log of the predictions before computing the RMSE

C.

They should evaluate the MSE of the log predictions to compute the RMSE

D.

They should exponentiate the predictions before computing the RMSE

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