NONLINEAR SYSTEM IDENTIFICATION FOR CLASS PREDICTION IN BIOINFORMATICS AND RELATED APPLICATIONS

摘要

The present invention provides a method for class prediction in bioinformatics based on identifying a nonlinear system that has been defined for carrying out a given classification task. Information characteristic of exemplars from the classes to be distinguished is used to create training inputs, and the training outputs are representative of the class distinctions to be made. Nonlinear systems are found to approximate the defined input/output relations, and these nonlinear systems are then used to classify new data samples. In another aspect of the invention, information characteristic of exemplars from one class are used to create a training input and output. A nonlinear system is found to approximate the created input/output relation and thus represent the class, and together with nonlinear systems found to represent the other classes, is used to classify new data samples.