Filtering, Robust Filtering, Polishing: Techniques for Addressing Quality in Software Data

摘要

Data quality is an important aspect of empirical analysis. This paper compares three noise handling methods to assess the benefit of identifying and either filtering or editing problematic instances. We compare a ''do nothing'' strategy with (i) filtering