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HAN 09-ch02-039-082-9780123814791


          58    Chapter 2 Getting to Know Your Data          2011/6/1  3:15  Page 58  #20













                           (a) Hilbert curve  (b) Gray code  (c) Z-curve

              Figure 2.11 Some frequently used 2-D space-filling curves.



                         One data
                         record          Dim 6
                                                                           Dim 6
                             Dim 5                   Dim 1
                                                                 Dim 5                Dim 1




                                                                 Dim 4                Dim 2
                             Dim 4                   Dim 2

                                                                           Dim 3
                                         Dim 3
                                                                            (b)
                                          (a)

              Figure 2.12 The circle segment technique. (a) Representing a data record in circle segments. (b) Laying
                         out pixels in circle segments.



                         to fill the windows. A space-filling curve is a curve with a range that covers the entire
                         n-dimensional unit hypercube. Since the visualization windows are 2-D, we can use any
                         2-D space-filling curve. Figure 2.11 shows some frequently used 2-D space-filling curves.
                           Note that the windows do not have to be rectangular. For example, the circle segment
                         technique uses windows in the shape of segments of a circle, as illustrated in Figure 2.12.
                         This technique can ease the comparison of dimensions because the dimension windows
                         are located side by side and form a circle.


                   2.3.2 Geometric Projection Visualization Techniques
                         A drawback of pixel-oriented visualization techniques is that they cannot help us much
                         in understanding the distribution of data in a multidimensional space. For example, they
                         do not show whether there is a dense area in a multidimensional subspace. Geometric
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