Name
Abstract | ||
|---|---|---|
We present NML models for discrete models and show how to apply the Minimum Description Principle to them to obtain structure information. Then we summarize methods derived in our previous works, and we treat in a unified manner all the usual discrete models. In the last part we describe important applications of the proposed models to disease classification. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ISSPA.2007.4555629 | ISSPA |
Keywords | Field | DocType |
diseases,genetics,matrix algebra,maximum likelihood estimation,medical computing,pattern classification,NML models,discrete models,disease classification,genomics,matrix algebra,minimum description principle,normalized maximum likelihood models,structure information | Disease classification,Data modeling,Pattern recognition,Matrix algebra,Computer science,Maximum likelihood,Algorithm,Genomics,Normalized maximum likelihood,Artificial intelligence,Machine learning | Conference |
Citations | PageRank | References |
1 | 0.36 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ioan Tabus | 1 | 276 | 38.23 |
| Jorma Rissanen | 2 | 1665 | 798.14 |
| Jaakko Astola | 3 | 1515 | 230.41 |