A separation algorithm applicable to the pattern classification and
cluster analysis of n-dimensional (n > 2) data is presented. The algorithm
reduces the dimensionality of the problem by projecting each point into
a plane. This plane is presented to the user on a computer graphics
console screen. The operator picks a point on the screen with a lightpen
and chooses a "direction of movement" to achieve or increase separation,
thereby causing an iteration of the algorithm. Each iteration is in fact
a reorientation of the plane into which the data points are projected.
Iterations continue until satisfactory separation is achieved. The
algorithm is not restricted by the dimensionality of the data, nor are any
distributional assumptions required. Results from six case studies
indicate that the algorithm is a useful tool for the analysis of multidimensional
data.http://archive.org/details/acomputergraphic1094516531Lieutenant, United States NavyApproved for public release; distribution is unlimited
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