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Dimensionality Reduction for Data Visualization

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Figure

Figure 1: A visualization can have two kinds of errors (from [9]). When a neighborhood P i in the high-dimensional input space is compared to a neighborhood Q i in the visualization, false positives are points that appear to be neighbors in the visualizati
Figure 2: Tradeoff between precision and recall in visualizing a sphere (from [9]). Left: the three- three-dimensional location of points on the three-three-dimensional sphere is encoded into colors and glyph shapes
Figure 3: A visual information retrieval interface to a collection of microarray experiments visualized as glyphs on a plane (from [14])
Figure 4: Visualizations of graphs. A: US college football teams (nodes) and who they played against (edges)

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