Mapping multidimensional space to one dimension for computer output display
ACM '68 Proceedings of the 1968 23rd ACM national conference
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
A pattern recognition program that generates, evaluates, and adjusts its own operators
IRE-AIEE-ACM '61 (Western) Papers presented at the May 9-11, 1961, western joint IRE-AIEE-ACM computer conference
Projections of multidimensional data for use in man-computer graphics
AFIPS '68 (Fall, part I) Proceedings of the December 9-11, 1968, fall joint computer conference, part I
Feature Evalution with Measures of Probabilistic Dependence
IEEE Transactions on Computers
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It is known that R linearly separable classes of multidimensional pattern vectors can always be represented in a feature space of at most R dimensions. An approach is developed which can frequently be used to find a nonorthogonal transformation to project the patterns into a feature space of considerably lower dimensionality. Examples involving classification of handwritten and printed digits are used to illustrate the technique.