Abstract: A neural classifier that allows visualization of the query, the training data and the decision regions in a single two-dimensional display, providing benefits for both the designer and the user. The visual neural classifier is formed from a set of experts and a visualization network. Visualization is accomplished by a funnel-shaped multilayer dimensionality reduction network configured to learn one or more classification tasks. If a single dimensionality reduction network does not provide sufficiently accurate classification results, a group of these dimensionality reduction networks may be arranged in a modular architecture. Among these dimensionality reduction networks, the experts receive the input data and the visualization network combines the decisions of the experts to form the final classification decision.