\begin{table}%T6
\caption{The confusion matrix for the Bayesian model averaging of artificial
neural networks and the two class problem.  The last but one line lists the
total number of light curves (TOT) to define every class. The last line lists
the correct classification rate (CC) for every class separately as measured by
10-fold cross validation. Separation between: A: eclipsing binaries (ECL) and
all other types; B: Cepheids (CEP) and all other types; C: long period variables
(LPV) and all other types except ECL and CEP; D: RR Lyrae stars (RR) from all
other types except ECL, CEP and LPV.  }
\label{seq1}
%%\centering
\par
\begin{tabular}{lcc|lcc|lcc|lcc}
\hline\hline
\multicolumn{3}{c|}{A} & \multicolumn{3}{c|}{B} & 
\multicolumn{3}{c|}{C} & \multicolumn{3}{c}{D} \\
\hline
  & ECL & REST &  & CEP & REST &  & LPV & REST &   & RR & REST \\
 \hline
 ECL & 374 & 2  & CEP & 302 & 18 &  LPV & 164 & 18 & RR & 205 & 8 \\ 
 REST & 1 & 1377 & REST & 25 & 1034 &  REST & 23 & 847 &  REST & 10 & 642 \\
 TOT & 375 & 1379 & TOT & 327 & 1052 &  TOT & 187 & 865 &  TOT & 215 & 650 \\
 CC (\%) & 99.73 & 99.85 &  CC (\%) & 92.35 & 98.28 &  CC (\%) & 
87.70 & 97.91 &  CC (\%) & 95.34 & 98.76 \\
 \hline
\end{tabular}
\end{table}