Name
Abstract | ||
|---|---|---|
The paper describes a model for a predictability analysis of various data types, which may be used to manage different real information systems. The models are “adaptive” in a sense of an absence of the fundamental assumptions about the probability distributions of the data. We present a special software tool based on the method of moving separation of the finite probability mixtures to ascertain the possibility of forecasting for the data. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICUMT.2015.7382428 | 2015 7th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT) |
Keywords | Field | DocType |
finite probability mixtures,moving separation,probability distributions,real information systems,predictability analysis | Software tool,Information system,Data mining,Predictability,Applied probability,Computer science,Probability distribution,Data type,Artificial intelligence,Machine learning | Conference |
ISSN | Citations | PageRank |
2157-0221 | 0 | 0.34 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergey Frenkel | 1 | 5 | 3.17 |
| Andrey Gorshenin | 2 | 1 | 3.67 |
| Victor Korolev | 3 | 16 | 11.26 |