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\@writefile{toc}{\contentsline {section}{\numberline {3}Datasets}{\thepage }}
\@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces 3 datasets used in this research contain a total of 237 projects. Datasets have different characteristics in terms of the number of attributes as well as the measures of these attributes.}}{\thepage }}
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\@writefile{toc}{\contentsline {section}{\numberline {4}Analysis of Datasets}{\thepage }}
\@writefile{toc}{\contentsline {subsection}{\numberline {4.1}PPR-Metrics Analysis}{\thepage }}
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\@writefile{lof}{\contentsline {figure}{\numberline {2}{\ignorespaces The PPR-metrics for Cocomo81 and Nasa93 datasets.}}{\thepage }}
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\@writefile{lof}{\contentsline {figure}{\numberline {3}{\ignorespaces The PPR-metrics for Desharnais dataset.}}{\thepage }}
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\@writefile{lof}{\contentsline {figure}{\numberline {4}{\ignorespaces The percentage distribution of all features to PPR-metrics for Cocomo81, Nasa93 and Desharnais dataset.}}{\thepage }}
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\@writefile{toc}{\contentsline {subsection}{\numberline {4.2}R-Square Analysis}{\thepage }}
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\@writefile{lof}{\contentsline {figure}{\numberline {5}{\ignorespaces The R-square values for Cocomo81 and Nasa93 datasets. R-square values are sorted in a descending order. All the R-Square values are low to suggest a significant meaning. However, the highest R-Square value belongs to LOC, which means that LOC can better explain the variations in the dependent variable when compared to other attributes.}}{\thepage }}
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\@writefile{lof}{\contentsline {figure}{\numberline {6}{\ignorespaces The R-square values for Desharnais dataset. R-square values are sorted in a descending order.}}{\thepage }}
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\@writefile{toc}{\contentsline {subsection}{\numberline {4.3}Feature Selection Analysis}{\thepage }}
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\@writefile{lof}{\contentsline {figure}{\numberline {7}{\ignorespaces Wrapper results compared with R-Square analysis for all datasets. Starting from the highest R-Square-scored features, we selected out as many features as those that were selected by wrapper. The dark-highlighted cells are the ones that are common in R-square analysis and wrapper.}}{\thepage }}
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\@writefile{toc}{\contentsline {section}{\numberline {5}Results}{\thepage }}
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\@writefile{toc}{\contentsline {subsection}{\numberline {5.1}Cocomo81}{\thepage }}
\@writefile{toc}{\contentsline {subsection}{\numberline {5.2}Nasa93}{\thepage }}
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\bibcite{Alpaydin2004}{1}
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\@writefile{toc}{\contentsline {subsection}{\numberline {5.3}Desharnais}{\thepage }}
\@writefile{toc}{\contentsline {section}{\numberline {6}Threats to Validity}{\thepage }}
\@writefile{toc}{\contentsline {section}{\numberline {7}Conclusion}{\thepage }}
\@writefile{toc}{\contentsline {section}{\numberline {8}References}{\thepage }}
\bibcite{Douglas1960}{5}
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\bibcite{Jorgensen2009}{9}
\bibcite{Kitchenham1993}{10}
\bibcite{Kitchenham2009}{11}
\bibcite{Kitchenham2007}{12}
\bibcite{koc10}{13}
\bibcite{Kultur2008}{14}
\bibcite{Lum2008}{15}
\bibcite{Menzies2006}{16}
\bibcite{Menzies2005b}{17}
\bibcite{Shepperd2007}{18}
\bibcite{Kadoda2001}{19}