A geometric-based data reduction approach for large low dimensional datasets: Delaunay triangulation in SVM algorithms
Training a support vector machine (SVM) on large datasets is a slow daunting process. Further, SVM becomes slow in the testing phase, due to its large number of support vectors (SVs). This paper proposes an effective geometric algorithm based on construction of Delaunay triangulation (DT) algorithm...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-06-01
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| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827021000062 |