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https://www.researchgate.net/publication/2461310_Model_Selection_for_Support_Vector_Machines
Model Selection for Support Vector Machines. ... In this paper we propose an automatic and effective model selection method. It is based on evolutionary computation algorithms and use recall ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.32.5059
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Automatic model selection is an important issue to make support vector machines (SVM) practically useful. Most existing approaches use the leave-one-out (loo) related estimators. As nding the loo rate is time consuming, researchers exploit dierent techniques to approximate it.
https://en.wikipedia.org/wiki/Support-vector_machine
In machine learning, support-vector machines (SVMs, also support-vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.Given a set of training examples, each marked as belonging to one or the other of two categories, an SVM training algorithm builds a model that assigns new examples to one category ...
https://www.sciencedirect.com/science/article/pii/S0925231203003758
We address the problem of model selection for Support Vector Machine (SVM) classification. For fixed functional form of the kernel, model selection amounts to tuning kernel parameters and the slack penalty coefficient C.We begin by reviewing a recently developed probabilistic framework for SVM classification.Cited by: 206
http://www.personal.psu.edu/users/j/x/jxz203/lin/Lin_pub/2007_COMSTAT.pdf
model selection. A nested uniform design (UD) methodology is proposed for ef cient, robust and automatic model selection for support vector machines (SVMs). The proposed method is applied to select the candidate set of parameter combinations and carry
https://dsmilab.github.io/Yuh-Jye-Lee/assets/file/publications/journal_papers/J14_Model%20Selection%20for%20Support%20Vector%20Machines%20via%20Uniform%20Design.pdf
formance in a learning task is the so-called model selection. A nested uniform design (UD) methodology is proposed for efficient, robust and automatic model selection for support vector machines (SVMs). The proposed method is applied to select the candidate set of parameter combinations and carry out a k-fold cross-validation to
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