How to calculate slack variables in SVM?
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| Papers (11) | Insight |
|---|---|
22 Mar 2010 18 Citations | The results indicate that our method can achieve an average improvements of 33.16% on the worst slack (WS) and 75.56% on the total negative slack (TNS), respectively. |
| The slack variable also enables explicit computation of a near-optimal, feasible starting point. | |
| We demonstrate that the SVM is a valuable tool and show that an automated discovery- significance based optimization of the SVM hyper-parameters is a highly efficient way to prepare an SVM for such applications. | |
28 Dec 2009 7 Citations | By using different penalty parameters to different slack variables in P-SVM, the new algorithm adjusts penalty parameters more flexible, and effectively improves the low classification accuracy caused by imbalanced samples. |
27 Citations | The presented evaluation shows that the Slack Method is superior to list-processing-based approaches with regard to both finding more feasible solutions as well as finding solutions with better objective function values. In a comparative survey we evaluate the Slack Method against several alternative allocation techniques. |
| This paper proposes an effective way to use the TY slack for successful statistical optimization. | |
| Increasing the values of slack variables, help in reducing the effect of noisy support vectors. | |
30 Aug 2011 32 Citations | In this paper we argue that the SVDD slack variables lack a clear geometric meaning, and we therefore re-analyze the cost function to get a better insight into the characteristics of the solution. |
30 Aug 2011 32 Citations | We also introduce and analyze two new definitions of slack variables and show that one of the proposed methods behaves more robustly with respect to outliers, thus providing tighter bounds compared to SVDD. |
| Moreover, we present a significantly simpler version of the Slack-Algorithm and also simplify its analysis. | |
45 Citations | We show that this formulation contains some unnecessary circuits which, furthermore, can fail to provide the correct value of one of the SVM parameters and suggest how to avoid these drawbacks. |
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