Automatic Model Selection Support Vector Machines

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Automatic Model Selection for Support Vector Machines ...

    https://www.researchgate.net/publication/2439541_Automatic_Model_Selection_for_Support_Vector_Machines
    Request PDF Automatic Model Selection for Support Vector Machines Automatic model selection is an important issue to make support vector machines …

Automatic Model Selection for Support Vector Machines (2000)

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.32.5059
    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.

Model Selection for Support Vector Machines via Uniform …

    https://research.cs.wisc.edu/areas/ai/airg/papers.fall07/huang.etal.model.selection.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

Model selection for support vector machines via uniform ...

    https://www.sciencedirect.com/science/article/pii/S0167947307000552
    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 evaluate the generalization performance of each parameter combination.Cited by: 192

Automatic Model Selection for Support Vector Machines - CORE

    http://core.ac.uk/display/22831132
    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.

Model selection for support vector machines via uniform ...

    https://www.semanticscholar.org/paper/Model-selection-for-support-vector-machines-via-Huang-Lee/bbaacb0bbf6127f32bfa6f303ba278fe43075eae
    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 evaluate the generalization performance of each parameter combination.

Model selection for support vector machines via uniform design

    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

Model Selection for Support Vector Machine Classification

    https://arxiv.org/pdf/cond-mat/0203334.pdf
    Keywords: Support Vector Machines, model selection, probabilistic methods, Bayesian evidence 1 Introduction Support Vector Machines (SVMs) have emerged in recent years as powerful techniques both for regression and classification. One of the central open questions is model selection: how does one tune the parameters of the SVM

Model Selection for Support Vector Machines Request PDF

    https://www.researchgate.net/publication/2461310_Model_Selection_for_Support_Vector_Machines
    Model selection in Support Vector machines is usually carried out by minimizing the quotient of the radius of the smallest enclosing sphere of the data and the observed margin on the training set.

Support-vector machine - Wikipedia

    https://en.wikipedia.org/wiki/Support-vector_machine
    In machine learning, support-vector machines 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 or the other, making it a non-probabilistic binary linear classifier. An SVM model …



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