Artikel

Robust linear classifier for unequal cost ratios of misclassification

This paper focuses on the robust classification procedures when the assumption of equal cost of misclassification is violated. A normal distribution based data set is generated using the Statistical Analysis System (SAS) version 9.1. Using Barlett's approximation to chi-square, the data set was found to be homogenous and was subjected to three linear classifiers namely: Maximum Likelihood Discriminant Function (MLDF), Fisher's linear Discriminant Function and Distance Based Discriminant Function. To Judge the performances of these procedures, the Apparent Error Rates for each procedure is obtained for different cost ratios 1:1, 1:2, 1:3, 1:4 and 1:5 and sample sizes 5:5, 10:10, 20:20, 30:30, and 50:50. The results shows that the three procedures are insensitive to cost ratio exceeding ratio 1:2 and that MLDF was observed as robust discriminant function among classification functions considered.

Sprache
Englisch

Erschienen in
Journal: CBN Journal of Applied Statistics ; ISSN: 2476-8472 ; Volume: 02 ; Year: 2011 ; Issue: 1 ; Pages: 51-59 ; Abuja: The Central Bank of Nigeria

Klassifikation
Wirtschaft
Thema
Apparent Error Rates
Maximum Likelihood Discriminant Function
Distance Based Discriminant Function
Fisher's linear

Ereignis
Geistige Schöpfung
(wer)
Ariyo, Oludare S.
Adebanji, A. O.
Ereignis
Veröffentlichung
(wer)
The Central Bank of Nigeria
(wo)
Abuja
(wann)
2011

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

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Objekttyp

  • Artikel

Beteiligte

  • Ariyo, Oludare S.
  • Adebanji, A. O.
  • The Central Bank of Nigeria

Entstanden

  • 2011

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