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Statistical Pattern Classification with Binary Variables
February 1981 (vol. 3 no. 2)
pp. 155-163
Tzay Y. Young, SENIOR MEMBER, IEEE, Department of Electrical Engineering, University of Miami, Coral Gables, FL 33124.
Philip S. Liu, MEMBER, IEEE, Department of Electrical Engineering, University of Miami, Coral Gables, FL 33124.
Romulo J. Rondon, Department of Electrical Engineering, University of Miami, Coral Gables, FL 33124; Engineering Department, Ford Motor de Venezuela, Valencia, Venezuela.
Binary random variables are regarded as random vectors in a binary-field (modulo-2) linear vector space. A characteristic function is defined and related results derived using this formulation. Minimax estimation of probability distributions using an entropy criterion is investigated, which leads to an A-distribution and bilinear discriminant functions. Nonparametric classification approaches using Hamming distances and their asymptotic properties are discussed. Experimental results are presented.
Citation:
Tzay Y. Young, Philip S. Liu, Romulo J. Rondon, "Statistical Pattern Classification with Binary Variables," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 3, no. 2, pp. 155-163, Feb. 1981, doi:10.1109/TPAMI.1981.4767073
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