Name
Title | ||
|---|---|---|
Semi-Supervised Classification with Spectral Projection of Multiplicatively Modulated Similarity Data |
Abstract | ||
|---|---|---|
A simple and efficient semi-supervised classification method is presented. An unsupervised spectral mapping method is extended to a semi-supervised situation with multiplicative modulation of similarities between data. Our proposed algorithm is derived by linearization of this nonlinear semi-supervised mapping method. Experiments using the proposed method for some public benchmark data and color image data reveal that our method outperforms a supervised algorithm using the linear discriminant analysis and a previous semi-supervised classification method. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1093/ietisy/e90-d.9.1456 | IEICE Transactions |
Keywords | Field | DocType |
nonlinear semi-supervised mapping method,multiplicatively modulated similarity data,public benchmark data,supervised algorithm,spectral projection,efficient semi-supervised classification method,semi-supervised situation,proposed algorithm,color image data,previous semi-supervised classification method,unsupervised spectral mapping method,semi-supervised classification | Similitude,Nonlinear system,Multiplicative function,Pattern recognition,Computer science,Modulation,Artificial intelligence,Spectral method,Linear discriminant analysis,Linearization,Color image | Journal |
Volume | Issue | ISSN |
E90-D | 9 | 1745-1361 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weiwei Du | 1 | 23 | 7.33 |
| Kiichi Urahama | 2 | 141 | 32.64 |