The object of this paper is to consider a very deep penetration of the requirements of effective learning algorithms of neural networks in predprotsessornoy processing. Developed a method for assessing the adequacy of neural network models in the absence of any a priori information about the distribution of noise in the data. This method allowed us to control quality predprotsessornoy interconnected data processing and quality of their approximation to the neural network