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» Data selection for support vector machine classifiers
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BMCBI
2006
169views more  BMCBI 2006»
14 years 10 months ago
Machine learning techniques in disease forecasting: a case study on rice blast prediction
Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
IVC
2006
259views more  IVC 2006»
14 years 10 months ago
Object detection using spatial histogram features
In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, th...
Hongming Zhang, Wen Gao, Xilin Chen, Debin Zhao
ESANN
2006
14 years 11 months ago
Degeneracy in model selection for SVMs with radial Gaussian kernel
We consider the model selection problem for support vector machines applied to binary classification. As the data generating process is unknown, we have to rely on heuristics as mo...
Tobias Glasmachers
PAMI
2010
132views more  PAMI 2010»
14 years 8 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel
WWW
2005
ACM
15 years 10 months ago
Boosting SVM classifiers by ensemble
By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a ch...
Yan-Shi Dong, Ke-Song Han