Name
Abstract | ||
|---|---|---|
In this paper we propose a new method for data mining prediction improvement. There are many prediction models with different advantages. Each model brings some positive as well as some negative features in terms of prediction quality. Different criteria can indicate different models as the best solution. Our aim is to utilize results from many models, identify common destructive components as precisely as possible and eliminate them. This will be done by Independent Component Analysis (ICA). The modified ICA -algorithm for effective problem solving will be proposed. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-39985-8_13 | INTELLIGENT INFORMATION PROCESSING AND WEB MINING |
Keywords | DocType | ISSN |
data mining,independent component analysis | Conference | 1615-3871 |
Citations | PageRank | References |
1 | 0.41 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryszard Szupiluk | 1 | 38 | 8.97 |
| Piotr Wojewnik | 2 | 20 | 6.32 |
| Tomasz Zabkowski | 3 | 32 | 11.28 |