How much did using standard deviations instead of minimum and maximum values affect the parallelepiped classification?
O) Compare each of the classifications you created: MAX, RAW, MFNSTD, PIPEORIG, and PIPEDST. To do this, display all of them with the Qualitative 256 palette. You may wish to use a smaller expansion factor to fit them all on the screen. As a final note, consider the following. If your training sites are very good, the Maximum Likelihood classifier should produce the best result. However, when training sites are not well defined, it often performs very poorly. In these cases, the Minimum Distance classifier with the standardized distances option often performs much better. The Parallelepiped classifier with the standard deviation option also performs rather well and is the fastest of the considered classifiers. When you have answered the 5 questions above, print one of your classifications formatted as a C-size document using the Designjet plotter and submit it with your word document. Aces… This activity is due at the end of class Wednesday, March 4. This lab activity incorporated pa
