Parsimonious least squares support vector regression using orthogonal forward selection with the generalised kernel model
نویسندگان
چکیده
منابع مشابه
Parsimonious least squares support vector regression using orthogonal forward selection with the generalised kernel model
A sparse regression modelling technique is developed using a generalised kernel model in which each kernel regressor has its individually tuned position (centre) vector and diagonal covariance matrix. An orthogonal least squares forward selection procedure is employed to append the regressors one by one. After the determination of the model structure, namely the selection of an appropriate numb...
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Sparse regression modeling is addressed using a generalized kernel model in which kernel regressor has its individually tuned position (center) vector and diagonal covariance matrix. An orthogonal least squares forward selection procedure is employed to append regressors one by one. After the determination of the model structure, namely the selection certain number of regressors, the model weig...
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This paper considers sparse regression modelling using a generalised kernel model in which each kernel regressor has its individually tuned centre vector and diagonal covariance matrix. An orthogonal least squares forward selection procedure is employed to select the regressors one by one, so as to determine the model structure. After the regressor selection, the corresponding model weight para...
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The objective of modelling from data is not that the model simply fits the training data well. Rather, the goodness of a model is characterized by its generalization capability, interpretability and ease for knowledge extraction. All these desired properties depend crucially on the ability to construct appropriate parsimonious models by the modelling process, and a basic principle in practical ...
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The objective of modelling from data is not that the model simply fits the training data well. Rather, the goodness of a model is characterized by its generalization capability, interpretability and ease for knowledge extraction. All these desired properties depend crucially on the ability to construct appropriate parsimonious models by the modelling process, and a basic principle in practical ...
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ژورنال
عنوان ژورنال: International Journal of Modelling, Identification and Control
سال: 2006
ISSN: 1746-6172,1746-6180
DOI: 10.1504/ijmic.2006.012612