Multiple Choice Flashcards on 01 Databricks Certified Machine Learning Associ...

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Flashcard Practice Databricks Certified Machine Learning Associate Multiple Choice

A team wants to median-impute numeric columns age and income while keeping the original columns available for audit. Which code pattern is most appropriate?

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df.na.drop(subset=["age", "income"]) before model training. VectorAssembler(inputCols=["age", "income"], outputCol="features").fit(df).transform(df). Imputer(strategy="mode", inputCols=["age", "income"], outputCols=["age", "income"]).fit(df).transform(df). Imputer(strategy="median", inputCols=["age", "income"], outputCols=["age_imputed", "income_imputed"]).fit(df).transform(df).

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