TY - JOUR
T1 - MULTIMEMBERSHIP AND MULTIPERSPECTIVE CLASSIFICATION
T2 - INTRODUCTION, APPLICATIONS, AND A BAYESIAN MODEL.
AU - Ben-Bassat, Moshe
PY - 1980
Y1 - 1980
N2 - Pattern recognition problems are introduced in which (1) the object to be recognized may simultaneously belong to several classes, which is called a multimembership classification (MMC), and (2) the object to be recognized has to be classified with respect to different groups of classes, which is called multiperspective classification (MPC). Possible applications of MMC and MPC models in medicine, bioengineering, military, and management are discussed. A Bayesian approach is developed which includes classification rules, feature selection, and performance measures.
AB - Pattern recognition problems are introduced in which (1) the object to be recognized may simultaneously belong to several classes, which is called a multimembership classification (MMC), and (2) the object to be recognized has to be classified with respect to different groups of classes, which is called multiperspective classification (MPC). Possible applications of MMC and MPC models in medicine, bioengineering, military, and management are discussed. A Bayesian approach is developed which includes classification rules, feature selection, and performance measures.
UR - http://www.scopus.com/inward/record.url?scp=0019026723&partnerID=8YFLogxK
U2 - 10.1109/tsmc.1980.4308507
DO - 10.1109/tsmc.1980.4308507
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AN - SCOPUS:0019026723
SN - 0018-9472
VL - SMC-10
SP - 331
EP - 336
JO - IEEE Transactions on Systems, Man and Cybernetics
JF - IEEE Transactions on Systems, Man and Cybernetics
IS - 6
ER -