On the question of the construction of cognitive maps for data mining

A method of constructing an optimal cognitive maps consists in optimizing the input data and the dimension data structure of a cognitive map. Pro-optimization problem occurs when large amounts of input data. Optimization of time-dimension data is clustering the input data and as a method of polarization-clusters using hierarchical agglomerative method. Cluster analysis allows to divide the data set into a finite number of homogeneous groups. Optimization of the structurery cognitive map is automatically tuning the balance of influence on each other concepts of machine learning methods, particularly the method of training the neural network.