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{\small
\centering
\begin{table}
\small
\centering
%\label{table-comp-all}
\caption{Comparison of One-class SVM (binary representation), 
Outlier-SVM (binary 
representation), Neural Networks (Hadamard representation),
         Naive Bayes, Nearest Neighbor (Hadamard representation),
         and  Prototype Algorithms ({\it tf-idf} representation). 
(Each method with the best representation tested.)
        }
\label{table-main-comp}                  
\footnotesize
\begin{tabular}{|l|l|l|l|l|l|l|}  

\hline 
       &One-class  &Outlier-  &Neural      &Naive    &Nearest  &Prototype \\  
       &SVM Radial &SVM       &Networks    &Bayes    &Neighbor  &      \\  
       &Basis      &Linear             &  &  &  &  \\
{\bf } &$F_1$ &$F_1$  &$F_1$  &$F_1$ &$F_1$ &$F_1$   \\ \hline \hline %  &$F_1$\\ 
 
Earn   &0.676 &0.750   &0.714   &0.708 &0.703  &0.637  \\ %  &0.673\\ 
Acq    &0.482 &0.504   &0.621   &0.503 &0.476  &0.468   \\ % &0.492\\ 
Money  &0.514 &0.563   &0.642   &0.493 &0.468  &0.484   \\ % &0.508\\
Grain  &0.585 &0.523   &0.473   &0.382 &0.333  &0.402   \\ % &0.409\\
Crude  &0.544 &0.474   &0.534   &0.457 &0.392  &0.398   \\ % &0.493\\ 
Trade  &0.597 &0.423   &0.569   &0.483 &0.441  &0.557    \\ %&0.441\\ 
Int    &0.485 &0.465   &0.487   &0.394 &0.295  &0.454   \\ % &0.379\\
Ship   &0.539 &0.402   &0.361   &0.288 &0.389  &0.370   \\ % &0.231\\
Wheat  &0.474 &0.389   &0.404   &0.288 &0.566  &0.262    \\ %&0.195\\
Corn   &0.298 &0.356   &0.324   &0.254 &0.168  &0.230   \\ \hline \hline 
%&0.353\\\hline
Avg    &0.519 &0.484   &0.513   &0.425 &0.423  &0.426   \\  \hline %&0.417\\
Macro  &0.572 &0.587   &0.615   &0.547  &0.530  &0.516  \\
\hline

\end{tabular}

\end{table}

} %%%END of SMALL


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