Detecting data leakage involves careful data auditing and validation checks. Researchers should:
Review the data collection processes to ensure no unnecessary information is being captured. Conduct cross-validation to ensure that the data used for training predictive models does not overlap with the test data. Analyze the temporal sequence of data to ensure that future information is not being used to predict past events.
