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\begin{document}
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\fig{css} generated as in the Lewis paper (using raw data with 1151 features):

\bi
\item the data is clustered to 3 clusters
\item the mean is found for each cluster and plotted
\ei

\fig{fs} generated using fastmapped data of 4 features. The values of each feature are plotted.

\begin{figure}[h!]
  \begin{center}
  \scalebox{0.97}{
    \begin{tabular}{c}
      \resizebox{100mm}{!}{\includegraphics{C1}} \\
      \resizebox{100mm}{!}{\includegraphics{C2}} \\
      \resizebox{100mm}{!}{\includegraphics{C3}} \\
     \end{tabular}}
    \caption{Infrared spectra of the mean of classes produced by kmeans clustering on 185 infrared spectra from 37 vehicles.}
    \label{fig:css}
  \end{center}
\end{figure}

\begin{figure}[h!]
  \begin{center}
  \scalebox{0.97}{
    \begin{tabular}{c}
      \resizebox{92mm}{!}{\includegraphics{f1a}} 
      \resizebox{92mm}{!}{\includegraphics{f2a}} \\
      \resizebox{92mm}{!}{\includegraphics{f3a}} 
      \resizebox{92mm}{!}{\includegraphics{f4a}} \\
    \end{tabular}}
    \caption{FastMapped infrared spectra for 4 features.}
    \label{fig:fs}
  \end{center}
\end{figure}



\begin{figure}
\begin{center}
\begin{tabular}{l@{~}|l@{~}|c@{~}| c@{~}|}
\cline{1-4}
Clusters & n & Final Instances & Reduction\% \\\hline
%\multirow{6}{*}{audio (226, 71, 24)} & n=1 & 36 & 19  \\
% & n=2 & 100 & 54 \\
% & n=4 & 100 & 54 \\
% & n=8 & 100 & 54 \\
% & n=16 & 100 & 54 \\
% \hline
\multirow{6}{*}{bc (286, 10, 2)} & n=1 & 272 & 95  \\
 & n=2 & 272 & 95 \\
 & n=4 & 200 & 70 \\
 & \colorbox{gray}{\color{white} n=7} & 58 & \colorbox{gray}{\color{white} 20} \\
 & n=8 & 8 & 3 \\
 & n=16 & 0 & 0 \\
  \hline
\multirow{6}{*}{heart (297, 14, 5)} & n=1 & 249 & 84  \\
 & n=2 & 200 & 67 \\
 & n=4 & 176 & 59 \\
 & n=8 & 64 & 22 \\
 & \colorbox{gray}{\color{white} n=9} & 35 & \colorbox{gray}{\color{white} 12} \\
 & n=16 & 0 & 0 \\
 \hline
\multirow{6}{*}{lym (148, 19, 4)} & n=1 & 120 & 81  \\
 & n=2 & 118 & 80 \\
 & n=4 & 115 & 78 \\
 & n=8 & 115 & 78 \\
 & n=16 & 32 & 22 \\
 & \colorbox{gray}{\color{white} n=17} & 20 & \colorbox{gray}{\color{white} 14} \\
  \hline 
\multirow{5}{*}{pima (768, 9, 2)} & n=1 & 375 & 49  \\
 & \colorbox{gray}{\color{white} n=2} & 95 & \colorbox{gray}{\color{white} 12} \\
 & n=4 & 13 & 2 \\
 & n=8 & 0 & 0 \\
 & n=16 & 0 & 0 \\
  \hline 
 \multirow{6}{*}{tumor (339, 18, 21)} & n=1 & 270 & 80  \\
 & n=2 & 255 & 75 \\
 & n=4 & 255 & 75 \\
 & n=8 & 255 & 75 \\
 & n=16 & 193 & 57 \\
 & \colorbox{gray}{\color{white} n=18} & 126 & \colorbox{gray}{\color{white} 37} \\
 \hline 
%\multirow{6}{*}{splice (3190, 61, 3)} & n=1 & 36 & 19  \\
% & n=2 & 100 & 54 \\
% & n=4 & 100 & 54 \\
% & n=8 & 100 & 54 \\
% & n=16 & 100 & 54 \\
%  \hline    
\end{tabular}
\end{center}
\caption{Instance selection using the CLIFF selector. The Reduction\% column shows the percentage of the original data set left after selection.}\label{fig:instances}
\end{figure}

\begin{figure}[h!]
  \begin{center}
  \scalebox{0.80}{
    \begin{tabular}{c}
      \resizebox{70mm}{!}{\includegraphics{bc-4}}
      \resizebox{70mm}{!}{\includegraphics{bc-7}}
      \resizebox{70mm}{!}{\includegraphics{bc-8}} \\
      \resizebox{70mm}{!}{\includegraphics{heart-4}}
      \resizebox{70mm}{!}{\includegraphics{heart-8}}
      \resizebox{70mm}{!}{\includegraphics{heart-9}} \\
      \resizebox{70mm}{!}{\includegraphics{lym-8}}
      \resizebox{70mm}{!}{\includegraphics{lym-16}}
      \resizebox{70mm}{!}{\includegraphics{lym-17}} \\
      \resizebox{70mm}{!}{\includegraphics{pima-1}}
      \resizebox{70mm}{!}{\includegraphics{pima-2}}
      \resizebox{70mm}{!}{\includegraphics{pima-4}} \\
      \end{tabular}}
    \caption{Breast Cancer, Heart, Lymph, Pima.}
    \label{fig:css}
  \end{center}
\end{figure}



\end{document}
