#==============================  
# Create synthetic classes
#==============================  
create.synthetic <- function(data.size) {
   # Set up samples
   X <- runif(data.size, -1, 1)
   Y <- runif(data.size, -1, 1)
   data <- cbind(X,Y)  # create an array of them
   # Set the target values

   tp <- matrix(0, data.size, 8)
   tp[,1] <- (X[]>=0)*1                     # 1 LHP, 0 otherwise
   tp[,2] <- (X[]*Y[]>=0)*1                 # 1 1st&4th Quad, 0 otherwise
   tp[,3] <- (X[]>=0)*1+ (X[]>=0 & Y[]>=0)*1 # 2 1st Quad, 1, 4th quad, 0 otherwise

   tp[,4] <- (X[]>=-Y[])*1                  # 1 to right of y = -x, 0 otherwise
   tp[,5] <- (X[]>=-Y[])&(X[]>=Y[])|(X[]<=-Y[])&(X[]<=Y[])*1  # 
   tp[,6] <- (X[]>=-Y[])*1+ ((X[]>=-Y[]) & X[]>=Y[])*1 #  rotated 2 1st Quad, 1, 4th quad, 0 otherwise

   tp[,7] <- (X[]^2+Y[]^2>=.25)*1           # 1 to right of y = -x, 0 otherwise

   tp[,8] <- (Y[]>=X[]^2+.25)*1             # 1 to above of y = x^2, 0 otherwise
   return(list(tp, data))
}