Встроенный метод отбора информативных признаков на основе двухэтапной схемы обучения нейросетевого нечеткого классификатора

The paper describes the embedded method of informative feature selection, based on two-stage training scheme of neural-fuzzy classifier. The method provides the possibility of separate feature set selection for every class of data, retaining the maximal classification accuracy, which is attained by applying modified technique of classifier parameter tuning.