\begin{optiontableAuto}
                     nkNN  &  \mc{1}{c}{--}  &               20  &  \mc{1}{l}{--}  &  Number of k-nearest neighbors \\
             BalanceDepth  &  \mc{1}{c}{--}  &                6  &  \mc{1}{l}{--}  &  Binary tree balance depth \\
                ScaleFrac  &  \mc{1}{c}{--}  &              0.8  &  \mc{1}{l}{--}  &  Fraction of events used to compute variable width \\
                SigmaFact  &  \mc{1}{c}{--}  &                1  &  \mc{1}{l}{--}  &  Scale factor for sigma in Gaussian kernel \\
                   Kernel  &  \mc{1}{c}{--}  &             Gaus  &  \mc{1}{l}{--}  &  Use polynomial (=Poln) or Gaussian (=Gaus) kernel \\
                     Trim  &  \mc{1}{c}{--}  &            False  &  \mc{1}{l}{--}  &  Use equal number of signal and background events \\
                UseKernel  &  \mc{1}{c}{--}  &            False  &  \mc{1}{l}{--}  &  Use polynomial kernel weight \\
                UseWeight  &  \mc{1}{c}{--}  &             True  &  \mc{1}{l}{--}  &  Use weight to count kNN events \\
                   UseLDA  &  \mc{1}{c}{--}  &            False  &  \mc{1}{l}{--}  &  Use local linear discriminant - experimental feature 
\end{optiontableAuto}
