Primary Large Sample Partitioning for Diagnosis and Recognition Problem Solving on the Basis of Computational Intelligence Methods - Subbotin, S. A. (Інститут проблем реєстрації інформації НАН України, 2013)
The new method of training and test sample forming from primary sample is proposed. It preserves in a generated sub-sample the most important topological properties of the original sample and did not even needs to load of the original sample into computer memory. It provides a sequential exemplar processing and performs transformation of the multi-dimensional coordinate set to the one-dimensional, which is also discretized to improve the data generalization properties. This allows to significantly reduce the sample size, and to significantly decrease the requirements to computer resources. Tabl.: 1. Refs: 12 titles.