Title :
Statistical Pattern Classification with Binary Variables
Author :
Young, Tzay Y. ; Liu, Philip S. ; Rondon, Romulo J.
Author_Institution :
SENIOR MEMBER, IEEE, Department of Electrical Engineering, University of Miami, Coral Gables, FL 33124.
fDate :
3/1/1981 12:00:00 AM
Abstract :
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.
Keywords :
Bioinformatics; Data analysis; Entropy; Error analysis; Minimax techniques; Pattern classification; Probability distribution; Random variables; Statistical analysis; Vectors; Binary data analysis; discriminant function; minimax estimation; pattern classification; statistical analysis;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1981.4767073
