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Chernoff face

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This example shows Chernoff faces for lawyers' ratings of twelve judges

Chernoff faces, invented by Herman Chernoff, display multivariate data in the shape of a human face. The individual parts, such as eyes, ears, mouth and nose represent values of the variables by their shape, size, placement and orientation. The idea behind using faces is that humans easily recognize faces and notice small changes without difficulty. Chernoff faces handle each variable differently. Because the features of the faces vary in perceived importance, the way in which variables are mapped to the features should be carefully chosen (eye size and eyebrow-slant have been found important)[1]

Asymmetry

In 1981, Bernhard Flury and Hans Riedwyl suggested 'asymmetrical' Chernoff faces; since a face has vertical symmetry (around the y-axis), the left side of the face is identical to the right and is basically wasted space. One could have the 18 variables that specify the left be one set of data, but use a different set of data for the right side of the face (allowing one face to depict 36 different datapoints.) They present results showing that such asymmetrical faces are useful in visualizing databases of identical twins, for example, and are useful in grouping as pairs of Chernoff faces would be.

References

  1. ^ "An Experimental Analysis of the Pre-Attentiveness of Features in Chernoff Faces", Morris CJ, Ebert DS, Rheingans P. 1999; published by the conference "Applied Imagery Pattern Recognition: 3D Visualization for Data Exploration and Decision Making". http://www.research.ibm.com/people/c/cjmorris/publications/Chernoff_990402.pdf
  • Herman Chernoff (1973). "The Use of Faces to Represent Points in K-Dimensional Space Graphically". Journal of the American Statistical Association. 68 (342). American Statistical Association: 361–368. doi:10.2307/2284077. JSTOR 10.2307/2284077.
  • Bernhard Flury and Hans Riedwyl (1981). "Graphical Representation of Multivariate Data by Means of Asymmetrical Faces". Journal of the American Statistical Association. 76 (376). American Statistical Association: 757–765. doi:10.2307/2287565. JSTOR 10.2307/2287565. {{cite journal}}: Unknown parameter |month= ignored (help)

Further reading