Name
Abstract | ||
|---|---|---|
In recent years, Support Vector Machines (SVM) have been extensively applied to deal with various data classification problems. However, in some cases, the application of SVM is limited due to the time taken to conduct model selection for SVM. This issue is of particular significant for some modern applications, such as web mining, in which the large-scale database is frequently updated. This paper proposes a data reduction based mechanism aimed at expediting the model selection process in SVM. Experimental results show that the proposed mechanism is able to greatly reduce the time taken to carry out model selection at minimum cost. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ICSMC.2003.1243910 | SMC |
Keywords | Field | DocType |
data reduction,model selection process,svm,data classification problems,large scale database,very large databases,web mining,support vector machines,support vector machine,model selection | Structured support vector machine,Data mining,Web mining,Computer science,Expediting,Support vector machine,Model selection,Artificial intelligence,Relevance vector machine,Data classification,Machine learning,Data reduction | Conference |
Volume | ISSN | ISBN |
1 | 1062-922X | 0-7803-7952-7 |
Citations | PageRank | References |
8 | 0.60 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu-Yen Ou | 1 | 252 | 16.78 |
| Chien-Yu Chen | 2 | 367 | 29.24 |
| Shien-ching Hwang | 3 | 141 | 10.55 |
| Yen-Jen Oyang | 4 | 423 | 48.82 |