Research support system for stochastic data processing
Andrey Konstantinovich Gorshenin, Victor Yu. Kuzmin · Pattern Recognition and Image Analysis · 2017
The paper describes a research support system named “MSM Tools” that can be used for stochastic modelling of real processes in various information systems and implements the heterogeneous computing paradigm. The proposed approach to data mining is based on method of moving separation of probability mixtures. To obtain statistical estimations of the unknown parameters of mixed probability models, the system implements several modifications of so-called EM algorithm (including grid modifications for the NVIDIA CUDA architecture) that are commonly used in such areas as pattern recognition, clustering, classification, processing of censored and/or truncated data. An example of real data analysis via “MSM Tools” service is given.