In [16] we presented a program named PNM which implements our projection methods (proposed in [15]). The control of PNM is carried out interactively. After a trial with PNM, the user analyzes the projection results (error rates, class-histograms, scatter plots) and, directed by them, chooses the type of projection (parametric or non-parametric) and the type of constraints for the discriminant vectors (ORTH or FREE) and defines the values of control parameters for a new trial. The control of the PNM is easily carried out by the use of instructions. The definitions and examples of the control instructions are described at length in the paper. In order to illustrate how the PNM-program can be used we describe an interactive classifier design concerning differential diagnoses of the cerebrovascular accident (CVA). In this application, the data set contains pathologo-anatomically verified CVA-cases with hemorrhages (91 cases) and infarction due to ischemia (122 cases). The best class-separation was achieved by the projection obtained by optimization of our non-parametric discriminant criterion, which was a consequence of the complicated structure of the CVA data.