Kuh, A., De Wilde, Philippe (2007) Comments on "Pruning error minimization in least squares support vector machines". IEEE Transactions on Neural Networks, 18 (2). pp. 606-609. ISSN 1045-9227. (doi:10.1109/TNN.2007.891590) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:93360)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: https://doi.org/10.1109/TNN.2007.891590 |
Abstract
In this letter, we comment on "Pruning Error Minimization in Least Squares Support Vector Machines"by B. J. de Kruif and T. J. A. de Vries. The original paper proposes a way of pruning training examples for least squares support vector machines (LS SVM) using no regularization (gamma = infin). This causes a problem as the derivation involves inverting a matrix that is often singular. We discuss a modification of this algorithm that prunes with regularization (γ finite and nonzero) and is also computationally more efficient.
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1109/TNN.2007.891590 |
| Uncontrolled keywords: | Least squares kernel methods, Online updating, Pruning, Regularization |
| Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, |
| Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
| Depositing User: | Philippe De Wilde |
| Date Deposited: | 20 Dec 2022 09:43 UTC |
| Last Modified: | 05 Nov 2024 12:58 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/93360 (The current URI for this page, for reference purposes) |
University of Kent Author Information
De Wilde, Philippe.
| Creator's ORCID: |
 https://orcid.org/0000-0002-4332-1715
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