
Ultimate access to all questions.
A data scientist has developed a three-class decision tree classifier using Spark ML and stored the predictions in a Spark DataFrame named preds_dt. The DataFrame has the schema: prediction DOUBLE, actual DOUBLE. Which code segment correctly calculates the model's accuracy from preds_dt and assigns it to the accuracy variable? Choose the best answer.
A
accuracy = MulticlassClassificationEvaluator(predictionCol="prediction", labelCol="actual", metricName="accuracy")
B
accuracy = RegressionEvaluator(predictionCol="prediction", labelCol="actual", metricName="accuracy")
C
classification_evaluator = MulticlassClassificationEvaluator(predictionCol="prediction", labelCol="actual", metricName="accuracy")_
D
accuracy = classification_evaluator.evaluate(preds_df)
E
accuracy = Summarizer(predictionCol="prediction", labelCol="actual", metricName="accuracy")
F
None