Name
Abstract | ||
|---|---|---|
This paper considers the classification problem using support vector (SV) machines and investigates how to maximally reduce the size of the training set without losing information. Under separable data set assumptions, we derive the exact conditions stating which observations can be discarded without diminishing the overall information content. For this purpose, we introduce the concept of potential SVs, i.e., those data that can become SVs when future data become available. To complement this, we also characterize the set of discardable vectors (DVs), i.e., those data that, given the current data set, can never become SVs. Thus, these vectors are useless for future training purposes and can eventually be removed without loss of information. Then, we provide an efficient algorithm based on linear programming that returns the potential and DVs by constructing a simplex tableau. Finally, we compare it with alternative algorithms available in the literature on some synthetic data as well as on data sets from standard repositories. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TNNLS.2013.2264731 | Neural Networks and Learning Systems, IEEE Transactions |
Keywords | Field | DocType |
linear programming,pattern classification,support vector machines,DV,SVM,discardable vectors,information content,linear programming,potential SV concept,separable classification problem,separable data set assumptions,simplex tableau,support vector machines,Data discardability conditions,discardable vectors,linear programming,potential support vectors,separable data sets,support vector machines | Training set,Data mining,Data set,Computer science,Support vector machine,Separable space,Simplex,Synthetic data,Artificial intelligence,Linear programming,Machine learning | Journal |
Volume | Issue | ISSN |
24 | 11 | 2162-237X |
Citations | PageRank | References |
0 | 0.34 | 28 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Damiano Varagnolo | 1 | 5 | 1.48 |
| Del Favero, S. | 2 | 10 | 2.24 |
| Francesco Dinuzzo | 3 | 261 | 16.03 |
| L. Schenato | 4 | 839 | 72.18 |