Determination of the spread parameter in the Gaussian kernel for classification and regression

By Wenjian Wang, Zongben Xu, Weizhen Lu, Xiaoyun Zhang. 2003

385 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Learning Explainable Decision Rules via Maximum Satisfiability (2020, background): “A popular choice is the Gaussian kernel [22] with cut-off parameter δ (although in practice we include a ﬁxed number of nearest neighbours).”
Enhancing one-class support vector machines for unsupervised anomaly detection (2013, background): “Finally, some kernels even allow SVMs to be considered as a dimensionality reduction technique [32].”
Comparative study of monthly inflow prediction methods for the Three Gorges Reservoir (2014, background): “But, Wang et al. (2003) indicated that prediction error is scarcely influenced by C. e is a trade-off between the sparseness of the representation and closeness to the data.”
Using Data Mining for Wine Quality Assessment (2009, methodology): “A practical method to set γ is to start the search from one of the extremes and then search towards the middle of the range while the predictive estimate increases [25].”