This paper proposes using the inter-cluster distance between class means in the feature space to help choose parameters for a kernel function when training ...
In this paper we propose using the inter-cluster distances in the feature spaces to choose the kernel parameters. Calculating such distance costs much less ...
In this paper we propose using the inter-cluster distances in the feature spaces to choose the kernel parameters. Calculating such distance costs much less ...
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Choosing the kernel parameters for support vector machines by the inter-cluster distance in the feature space · Fast tuning of SVM kernel parameter using ...
This paper proposes using the inter-cluster distance between class means in the feature space to help choose parameters for a kernel function when training ...
Kuo-Ping Wu, Sheng-De Wang: Choosing the Kernel parameters of Support Vector Machines According to the Inter-cluster Distance. IJCNN 2006: 1205-1211.
Apr 29, 2014 · The values {d,γ} and γ in the polynomial and gaussian kernels are the kernel parameters which need to be chosen optimally for the SVM. Presented ...
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Choosing the Kernel parameters of Support Vector Machines ...
colab.ws › articles › ijcnn.2006.246828
Choosing the Kernel parameters of Support Vector Machines According to the Inter-cluster Distance. Kuo-Ping Wu, Sheng-De Wang.
Choosing the Kernel Parameters for the Directed Acyclic Graph Support ...
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The most popular method to decide the kernel parameters is the grid search method. In the training process, classifiers are trained with different kernel ...
We propose calculating the inter-cluster distance in the feature space to help determine the kernel parameters for training the SVM models. The kernel ...