A relaxation method mapping high-dimensional sample points to low-dimensional sample points is discussed. This method tries to preserve the local interdistance of sample points. Some special heuristics have been introduced to handle the difficulty arising from a large amount of data. Experimental results with handwritten character data and Iris data show that the method runs fast, converges rapidly, and requires a small amount of memory space.
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Chang et al. (1973) studied this question.
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