Name
Abstract | ||
|---|---|---|
The paper describes an application of a one class KNN to identify different signal patterns embedded in a noise structured background. The problem becomes harder whenever only one pattern is well-represented in the signal; in such cases, one class classifier techniques are more indicated. The classification phase is applied after a preprocessing phase based on a multi layer model (MLM) that provides preliminary signal segmentation in an interval feature space. The one class KNN has been tested on synthetic and real (Saccharomyces cerevisiae) microarray data in the specific problem of DNA nucleosome and linker regions identification. Results have shown, in both cases, a good recognition rate. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1504/IJKESDP.2009.028989 | IJKESDP |
Keywords | Field | DocType |
good recognition rate,class knn,classification phase,different signal pattern,dna nucleosome,preprocessing phase,preliminary signal segmentation,signal identification,class classifier technique,biological case study,specific problem,saccharomyces cerevisiae,bioinformatics,microarray data,classification | Feature vector,Multi layer,Pattern recognition,Segmentation,Computer science,Preprocessor,Artificial intelligence,Classifier (linguistics),Machine learning | Journal |
Volume | Issue | Citations |
1 | 4 | 2 |
PageRank | References | Authors |
0.38 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vito Di Gesu | 1 | 3 | 0.82 |
| Giosue Lo Bosco | 2 | 4 | 1.45 |
| Luca Pinello | 3 | 49 | 7.71 |