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A Classification Rule Whose Probability of Misclassification is Independent of the Variance
Author(s) -
Adegboye O. S.
Publication year - 1987
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1987.tb00736.x
Subject(s) - statistics , variance (accounting) , mathematics , classification rule , sample (material) , artificial intelligence , computer science , physics , accounting , business , thermodynamics
Summary An observation × o is to be classified into one of two normal populations φ 1 and φ 2 . A classification rule, the Two‐stage sample Rule, R (TS), whose probability of misclassification, P [MC], is independent of the common but unknown variance is proposed. Some optimal properties of R (TS) are also discussed and some values of P[MC | R (TS)], the probability of misclassification given the rule R(TS), are tabulated.