Question
During a migration from notebooks to a scheduled Spark ML pipeline, validation accuracy drops because StringIndexer is fit separately in training and batch scoring jobs. What is the most likely problem?
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During a migration from notebooks to a scheduled Spark ML pipeline, validation accuracy drops because StringIndexer is fit separately in training and batch scoring jobs. What is the most likely problem?
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