Consider that the quality of the training dataset has a significant impact on models' performance on the test datasets.
in this paper, we propose a metric, C train:test , to measure the correlation degree between the training and test dataset by calculating the number of spelling errors that occur in them: where E train and E test refer to the set of spelling errors in the training dataset and the test dataset, respectively.