Double Labeling

Double labeling is a technique used to improve the accuracy of data or information by assigning two separate labels or identifiers to the same item. This process helps verify that the labels are correct, reducing errors and ensuring consistency. It is often used in research, machine learning, and data management to cross-check and validate data, leading to more reliable results. Essentially, by having two independent labels, any discrepancies can be identified and corrected, increasing confidence in the data’s correctness.