Name
Title | ||
|---|---|---|
A classifier based on normalized maximum likelihood model for classes of Boolean regression models |
Abstract | ||
|---|---|---|
Boolean regression models are useful tools for various applications in nonlinear filtering, nonlinear prediction, classification and clustering. We discuss here the so- called normalized maximum likelihood (NML) models for these classes of models. Examples of discrimination of cancer types by using the universal NML model for the Boolean regression models indicate its ability to se- lect sets of feature genes discriminating at error rates significantly smaller than those of other discrimination methods. |
Year | Venue | Keywords |
|---|---|---|
2002 | EUSIPCO | boolean functions,maximum likelihood detection,nonlinear filters,regression analysis,signal classification,boolean regression models,nml models,nonlinear classification,nonlinear clustering,nonlinear filtering,nonlinear prediction,normalized maximum likelihood model |
Field | DocType | ISSN |
Pattern recognition,Regression analysis,Nonlinear filtering,Normalized maximum likelihood,Artificial intelligence,Classifier (linguistics),Cluster analysis,Mathematics,Nonlinear prediction | Conference | 2219-5491 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| I. Tabus | 1 | 87 | 10.32 |
| Jorma Rissanen | 2 | 1665 | 798.14 |
| Jaakko Astola | 3 | 1515 | 230.41 |