In a result contrary to much recent work\cite{localitySDP,locality2,locality3}\label{pg:statement}, locality based classifiers such as RIPPER, Ridor, and LWL perform the same as, or worse than non-locality based classifiers such as C4.5, OneR, and Naive Bayes when used on software defect prediction datasets. Although locality can improve classification in many situations, current software defect prediction datasets do not lend themselves to the use of locality. I propose that approaches other than Euclidean distance based locality are explored when working with software defect prediction.
