Abstract | ||
---|---|---|
A new preprocessing method that has found considerable use for chemical applications is presented. Features are selected that are useful for class discrimination, orthogonal, and at least in part, retain identity to the original measurements. A brief introduction to chemical pattern recognition is presented followed by a description of the method and an application to mass spectral data analysis. |
Year | DOI | Venue |
---|---|---|
1976 | 10.1016/0031-3203(76)90023-6 | Pattern Recognition |
Keywords | Field | DocType |
Orthogonal feature selection,Pattern recognition,Mass spectrometry,Molecular structural features | Feature selection,Pattern recognition,Computer science,Speech recognition,Feature (machine learning),Spectral data,Preprocessor,Artificial intelligence,Class discrimination,Machine learning | Journal |
Volume | Issue | ISSN |
8 | 1 | 0031-3203 |
Citations | PageRank | References |
4 | 1.59 | 2 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
---|---|---|---|
B.R. Kowalski | 1 | 4 | 1.59 |
C.F. Bender | 2 | 4 | 1.59 |