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.