\relax 
\citation{Boetticher2007}
\citation{Kitchenham2007}
\citation{Turhan2009}
\citation{Shepperd1996}
\citation{Mendes2003}
\citation{Li2009}
\@writefile{toc}{\contentsline {section}{\numberline {1}Introduction}{\thepage }}
\@writefile{toc}{\contentsline {section}{\numberline {2}Relevancy Filtering}{\thepage }}
\newlabel{section:relevancy-filtering}{{2}{\thepage }}
\newlabel{equ:euclid}{{1}{\thepage }}
\citation{Turhan2009}
\citation{koc10}
\citation{koc10}
\citation{Boehm1981}
\citation{Desharnais1989}
\citation{Boetticher2007}
\@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces Two pass relevancy filtering. Each tree BT1 and BT2 are binary cluster trees. The red sub-tree is pruned in pass one due to high variance. The remaining subtrees (shown in green) form the right-hand tree. In pass two, test instances start at the root of this tree and traverse to the nearest child (and so on, recursively). While the sub-tree variance continues to decrease, the traversal continues. Estimates are generated from the median of the instances of the right-hand-side sub-tree with lowest variance. }}{\thepage }}
\newlabel{fig:filtering}{{1}{\thepage }}
\@writefile{toc}{\contentsline {section}{\numberline {3}Methodology}{\thepage }}
\newlabel{EquationMRE}{{2}{\thepage }}
\@writefile{toc}{\contentsline {section}{\numberline {4}Results}{\thepage }}
\@writefile{toc}{\contentsline {subsection}{\numberline {4.1}Without Relevancy Filtering}{\thepage }}
\newlabel{none}{{4.1}{\thepage }}
\@writefile{toc}{\contentsline {subsection}{\numberline {4.2}With Relevancy Filtering}{\thepage }}
\newlabel{with}{{4.2}{\thepage }}
\@writefile{lof}{\contentsline {figure}{\numberline {2}{\ignorespaces MRE win-tie-loss results without relevancy filtering. Every odd and even line is a pair of experiments. In each pair, there is a {\em  within} and a {\em  cross} experiment. In {\em  cross} experiment, a linear regression model is built on {\em  cross} data and tested on the {\em  within} data. In {\em  within} experiment, the test instance is selected with leave-one-out, and a linear regression model is built on the remaining instances and tested on the selected test instance. A ``1'' denotes which item in the pair won, lost or tied.}}{\thepage }}
\newlabel{fig:wltNoFiltering}{{2}{\thepage }}
\@writefile{lof}{\contentsline {figure}{\numberline {3}{\ignorespaces MRE win-tie-loss values for Nasa93 from 20 {\em  randomized assessments}. In all treatments $tie$ values are quite high. For Nasa93, the performance of {\em  cross} data is mostly same as {\em  within} data.}}{\thepage }}
\newlabel{fig:wltNasa93}{{3}{\thepage }}
\@writefile{lof}{\contentsline {figure}{\numberline {4}{\ignorespaces MRE win-tie-loss values for Cocomo81 from 20 {\em  randomized assessments}. In 2 treatments {\em  cross} data is the same as the {\em  within} data. However, in the case of Coc81o, {\em  within} outperforms {\em  cross} data.}}{\thepage }}
\newlabel{fig:wltCocomo81}{{4}{\thepage }}
\@writefile{lof}{\contentsline {figure}{\numberline {5}{\ignorespaces MRE win-tie-loss values for Desharnais from 20 {\em  randomized assessments}. In the case of DesL3 the {\em  within} data is much better than the {\em  cross} data. For other treatments, {\em  within} and {\em  cross} data are statistically the same.}}{\thepage }}
\newlabel{fig:wltDesharnais}{{5}{\thepage }}
\citation{chen09}
\bibstyle{abbrv}
\bibdata{myref}
\bibcite{Boehm1981}{1}
\bibcite{Boetticher2007}{2}
\bibcite{chen09}{3}
\bibcite{Desharnais1989}{4}
\bibcite{Kitchenham2007}{5}
\bibcite{koc10}{6}
\bibcite{Li2009}{7}
\bibcite{Mendes2003}{8}
\bibcite{Shepperd1996}{9}
\bibcite{Turhan2009}{10}
\@writefile{lof}{\contentsline {figure}{\numberline {6}{\ignorespaces Mean number of instances used for estimation after filtering in 20 runs. {\em  Cross} datasets are combinations of two {\em  within} datasets tested on another {\em  within} dataset. }}{\thepage }}
\newlabel{fig:srsize}{{6}{\thepage }}
\@writefile{toc}{\contentsline {section}{\numberline {5}Discussion}{\thepage }}
\@writefile{toc}{\contentsline {section}{\numberline {6}References}{\thepage }}