×

zbMATH — the first resource for mathematics

The effects of misclassification costs and skewed distributions in two-group classification. (English) Zbl 1079.62519
In this study, Monte Carlo simulation experiments were employed to examine the performance of four statistical two-group classification methods when the data distributions are skewed and misclassification costs are unequal, conditions frequently encountered in business and economic applications. The classification methods studied are linear and quadratic parametric, nearest neighbor and logistic regression methods. It was found that when skewness is moderate, the parametric methods tend to give best results. Depending on the specific data condition, when skewness is high, either the linear parametric, logistic regression, or the nearest-neighbor method gives the best results. When misclassification costs differ widely across groups, the linear parametric method is favored over the other methods for many of the data conditions studied.

MSC:
62H30 Classification and discrimination; cluster analysis (statistical aspects)
65C05 Monte Carlo methods
PDF BibTeX XML Cite
Full Text: DOI
References:
[1] Altman E., Applications of Classification Techniques in Business, Banking, and Finance (1980)
[2] DOI: 10.1080/02664768800000007
[3] DOI: 10.2307/2326320
[4] Johnson J.R., The Accounting Review 41 pp 270– (1981)
[5] DOI: 10.1111/j.1469-1809.1946.tb02368.x
[6] DOI: 10.1214/aoms/1177730030 · Zbl 0034.22804
[7] DOI: 10.1111/j.1469-1809.1936.tb02137.x
[8] DOI: 10.1002/0471725293
[9] DOI: 10.1093/biomet/59.1.19 · Zbl 0231.62080
[10] DOI: 10.1214/aoms/1177704472 · Zbl 0116.11302
[11] Hand D.J., Kernel Discriminant Analysis (1982) · Zbl 0562.62041
[12] Fix E., Discriminatory Analysis–Nonparametric Discrimination: Consistency Properties (1951) · Zbl 0715.62080
[13] Agrawala A.K., Machine Recognition of Patterns (1977)
[14] DOI: 10.2307/2289860
[15] DOI: 10.1016/S0167-9473(96)00043-6 · Zbl 0875.62266
[16] DOI: 10.1080/03610927308827006 · Zbl 0275.62054
[17] DOI: 10.2307/2285453 · Zbl 0319.62039
[18] DOI: 10.1016/0898-1221(86)90073-8 · Zbl 0589.62046
[19] DOI: 10.2307/2285696 · Zbl 0291.62073
[20] DOI: 10.1080/03610927908827830 · Zbl 0422.62061
[21] DOI: 10.2307/2286261 · Zbl 0399.62060
[22] DOI: 10.1080/00949658008810396 · Zbl 0459.62044
[23] DOI: 10.1111/j.1540-5915.1999.tb00902.x
[24] DOI: 10.1016/0898-1221(86)90076-3 · Zbl 0606.62060
[25] Kotz S., Distributions in Statistics: Continuous Multivariate Distributions, 1, 2. ed. (1972) · Zbl 0248.62021
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.