SLIDE 1
- By
- We need effective
By - - PowerPoint PPT Presentation
By - - PowerPoint PPT Presentation
By Mingyue Tan Mar10, 2004
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Paper Reviewed
Dimensional Anchors: a Graphic Primitive for
Multidimensional Multivariate Information Visualizations,
- P. Hoffman, G. Grinstein, & D. Prinkney, Proc. Workshop
- n New Paradigms in Information Visualization and
Manipulation, Nov. 1999, pp. 9-16.
Visualizing Multi-dimensional Clusters, Trends, and
Outliers using Star Coordinates, Eser Kandogan, Proc. KDD 2001
StarClass: Interactive Visual Classification Using Star
Coordinates , S. Teoh & K. Ma, Proc. SIAM 2003
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- contains car specs (eg. mpg, cylinders, weight,
acceleration, displacement, type(origin), horsepower, year, etc)
- type: American, Japanese, & European
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x y z w
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*#
- #
p1: size of the scatter plot points p2: length of the perpendicular lines extending from individual anchorpoints in a scatter plot p3: length of the lines connecting scatter plot points that are associated with the same data point p4: width of the rectangle in a survey plot p5: length of the parallel coordinate lines p6: blocking factor for the parallel coordinate lines p7: size of the radviz plot point p8: length of the “spring” lines extending from individual anchorpoints of a radviz plot p9: the zoom factor for the “spring” constant K
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()
- Dimension – miles per gallon
- Data values are mapped to the axis
- Mapped data points - anchorpoints, represent the
coord values(points along a DA)
- Lines extended from anchorpoints
- Color – type of car (American – red, Japanese –
green, and European – purple)
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12
2
- *
32#
- 4#$-
- p1: size of the scatter plot points
- p2: length of the perpendicular
lines extending from individual anchor points in a scatter plot
- p3: length of the lines connecting
scatter plot points that are associated with the same data point
P = (0.8, .2, 0, 0, 0, 0, 0, 0, 0)
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1
P = (0.6, 0, 0, 0, 0, 0, 0, 0, 0) P = (.6, 0, 1.0, 0, 0, 0, 0, 0, 0)
P3: length of lines connecting all displayed points associated with one real data point(record)
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p4: width of the
rectangle in a survey plot
CCCViz DAs with P = (0, 0, 0, 1.0, 0, 0, 0, 0, 0)
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*#
9#
2
- length of these connecting
lines is controlled by p5.
- p5 = 1.0, fully connected,
every anchorpoint connects to all the other (N-1) anchorpoints
*:2$
;
- p6 = 0, traditional PC
P = (0, 0, 0, 0, 1.0, 1.0, 0, 0, 0)
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Original Radviz – 3 overlapping points DAs spread polygon P = (0, 0, 0, 0, 0, 0, .5, 1.0, .5) 92 ##%%
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P=(v1, v2) P=(v1,v2,v3,v4,v5,v6,v7,v8) Mapping:
- Items dots
- attribute vectors position
v1
v2
d1 p
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Low weight, displacement, high acceleration cars
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- NY – outlier
- SF – comparable arts, ect,
but better climate and lower crime
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+#
Dimensional Anchors: a Graphic Primitive for
Multidimensional Multivariate Information Visualizations,
- P. Hoffman, G. Grinstein, & D. Prinkney, Proc. Workshop
- n New Paradigms in Information Visualization and
Manipulation, Nov. 1999, pp. 9-16.
Visualizing Multi-dimensional Clusters, Trends, and
Outliers using Star Coordinates, Eser Kandogan, Proc. KDD 2001
StarClass: Interactive Visual Classification Using Star
Coordinates , S. Teoh & K. Ma, Proc. SIAM 2003
http://graphics.cs.ucdavis.edu/~steoh/research/classificat