\begin{slide}{Eg2: Effort estimation}
	\bi
       \item NASA COCOMO data (\cite{boehm00b})
	\item Results from IEEE TSE  (\cite{me06d}).
	   \item learners for continuous classes
	   \item A study of 160 effort estimation methods
	   \item 20 * \{ pick any 10, train on remaining, test on 10 \}
     \ei 
{\footnotesize\begin{center}
\begin{tabular}{r|r|r|r} 
    \multicolumn{1}{c}{~} & \multicolumn{3}{c}{$100*(pred-actual)/actual$}\\\cline{2-4}
 		& 50\% percentile& 65\% percentile & 75\% percentile\\\hline
 mode= embedded & -9 & 26 & 60 \\
 project= X & -6 & 16 & 46 \\
 all & -4 & 12 & 31 \\
 year= 1975 & -3 & 19 & 39 \\ 
 mode= semi-detached & -3 & 10 & 22 \\
 ground systems  & -3 & 11 & 29 \\
 center= 5 & -3 & 20 & 50 \\
  mission planning & -1 & 25 & 50 \\
 project= gro & -1 & 9 & 19 \\
 center= 2 & 0 & 11 & 21 \\
 year= 1980 & 4 & 29 & 58 \\ 
 avionics monitoring & 6 & 32 & 56 \\\hline
 median & -3 & 19 & 39
	\end{tabular}
\end{center}}
\bi
\item i.e. usually, very accurate estimates
\ei
\end{slide}
%\begin{wideslide}{No ``best'' effort model}
%~\vspace{-1cm}
%\begin{center}
%\includegraphics[width=4.5in]{used.eps}
%\end{center}
%
%So the generation method is general, but the generated model is task-specific.

%\end{wideslide}

