Name
Abstract | ||
|---|---|---|
In this paper we apply a novel smooth component analysis algorithm as ensemble method for prediction improvement. When many prediction models are tested we can treat their results as multivariate variable with the latent components having constructive or destructive impact on prediction results. We show that elimination of those destructive components and proper mixing of those constructive can improve the final prediction results. The validity and high performance of our concept is presented on the problem of energy load prediction. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74494-8_35 | ICA |
Keywords | Field | DocType |
destructive component,smooth component analysis,latent component,ensemble method,prediction result,high performance,energy load prediction,prediction model,destructive impact,prediction improvement,final prediction result | Computer science,Constructive,Multivariate statistics,Independent component analysis,Artificial intelligence,Predictive modelling,Component analysis,Machine learning | Conference |
Volume | ISSN | ISBN |
4666 | 0302-9743 | 3-540-74493-2 |
Citations | PageRank | References |
4 | 0.78 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryszard Szupiluk | 1 | 38 | 8.97 |
| Piotr Wojewnik | 2 | 20 | 6.32 |
| Tomasz Zabkowski | 3 | 32 | 11.28 |