论文信息 - A coupling procedure for the discrimination of mixed data.

A coupling procedure for the discrimination of mixed data.

A procedure is described for coupling different discriminators to a new (common) decision rule using the corresponding allocation vectors only. This enables one to cope jointly with data of different structure and/or scales of measurement but without strong restrictions on the number of (especially categorical) features. The method is combined with a consequent cross-validation process securing the results reached. Examples from medical diagnostics demonstrate the usefulness of the proposed procedure, especially in comparison with the known linear discriminant analysis as judged from the error rates obtained.

K D Wernecke | K. Wernecke

[1] Wojtek J. Krzanowski,et al. Discrimination and Classification Using Both Binary and Continuous Variables , 1975 .

[2] M. R. Mickey,et al. Estimation of Error Rates in Discriminant Analysis , 1968 .

[3] J. Daudin,et al. Selection of variables in mixed-variable discriminant analysis , 1986 .

[4] F. H. C. Marriott,et al. Discrimination with Mixed Binary and Continuous Data , 1982 .

[5] Ingram Olkin,et al. Multivariate Correlation Models with Mixed Discrete and Continuous Variables , 1961 .

[6] Godfried T. Toussaint,et al. Bibliography on estimation of misclassification , 1974, IEEE Trans. Inf. Theory.

[7] K.‐D. Wernecke,et al. The Use of Combined Classifiers in Medical Functional Diagnostics , 1986 .

[8] W J Krzanowski,et al. Mixtures of continuous and categorical variables in discriminant analysis. , 1980, Biometrics.

[9] J. Aitchison,et al. Multivariate binary discrimination by the kernel method , 1976 .

[10] R. H. Shumway,et al. 1 Discriminant analysis for time series , 1982, Classification, Pattern Recognition and Reduction of Dimensionality.

[11] Wojtek J. Krzanowski,et al. Stepwise Location Model Choice in Mixed‐Variable Discrimination , 1983 .