Answer-first summary for fast verification
Answer: Relative Expression Split
For time series data, the correct splitting mode is Relative Expression Split (C) because it allows splitting based on date/time conditions, preserving the temporal order and preventing data leakage. Time series data has sequential dependencies, so random splitting (D) would disrupt the time sequence and potentially leak future information into training data. Regular Expression Split (B) is for text patterns, not numerical/time data. Recommender Split (A) is for recommendation systems, not time series. The community consensus strongly supports C with 67% of votes and high-upvoted comments explaining that time series requires non-random splitting by date to maintain integrity.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
You are working with a time series dataset in Azure Machine Learning Studio. You need to split the dataset into training and testing subsets using the Split Data module. Which splitting mode should you use?
A
Recommender Split
B
Regular Expression Split
C
Relative Expression Split
D
Split Rows with the Randomized split parameter set to true
No comments yet.