Clean, well-labeled datasets used for machine learning are partitioned into three subsets: Training sets, Validation...

CPMAI’s glossary defines data splitting as “dividing a data set into subsets (e.g., training, validation, test) for model development and evaluation,” typically achieved via random subsampling to ensure each subset is representative of the underlying distribution and to prevent sampling bias.