Name
Abstract | ||
|---|---|---|
In this paper we show that applying of multidimensional decompositions can improve the modelling results. The predictions usually consist of twofold elements, wanted and destructive ones. Rejecting of the destructive components should improve the model. The statistical methods like PCA and ICA with new modifications are employed. The example from the telecom market proofs correctness of the approach. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/3-540-32392-9_40 | INTELLIGENT INFORMATION PROCESSING AND WEB MINING, PROCEEDINGS |
Field | DocType | ISSN |
Data mining,Computer science,Correctness,Mathematical proof,Artificial intelligence,Independent component analysis,Stable distribution,Machine learning | Conference | 1615-3871 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryszard Szupiluk | 1 | 38 | 8.97 |
| Piotr Wojewnik | 2 | 20 | 6.32 |
| Tomasz Zabkowski | 3 | 32 | 11.28 |