The example shows the results from slow autopilot for a particular data set.
Because it had the "slow" setting of autopilot, it attempts 6D down through 1D solutions.

Several points to notice about these graphs:

• Curves for higher dimensionalities have lower final stress than curves for lower dimensionality.
  That is because it is easier to fit the data with more dimensions in the solution.
  
  
• Curves for the randomized runs have higher final stress values than the curves for the real runs.
  This is because the real data have a correlation structure among the variables that allows a lower stress solution.
  
  
• Curves for the real runs are more variable for a given dimensionality than the randomized runs.
  
  
• A few real curves have rather high instability, as shown by their jagged shape.