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67.988  Articles
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The single index support vector regression model (SI-SVR) is a useful regression technique used to alleviate the problem of high-dimensionality. In this paper, we propose a robust variable selection technique for the SI-SVR model by using vital method to ... see more

This paper describes the possibilities of variable selection in large-scale industrial systems. It introduces knowledge-based, data-based and model-based methods for this purpose. As an example, Case-Based Reasoning application for the evaluation of the w... see more

The single index support vector regression model (SI-SVR) is a useful regression technique used to alleviate the problem of high-dimensionality. In this paper, we propose a robust variable selection technique for the SI-SVR model by using vital method to ... see more

Variable selection is an important property of shrinkage methods. The adaptive lasso is an oracle procedure and can do consistent variable selection. In this paper, we provide an explanation that how use of adaptive weights make it possible for the adapti... see more

In this paper, we compare the method of Gunter et al. (2011) for variable selection in treatment comparison analysis (an approach to regression analysis where treatment-covariate interactions are deemed important) with a simple stepwise selection method t... see more

Determination of the input/output variables is an important issue in Data Envelopment Analysis (DEA). Researchers often refer to expert opinions in defining these variables. The purpose of this paper is to propose a new approach to determine the input/out... see more

Random forests are currently one of the most preferable methods of supervised learning among practitioners. Their popularity is influenced by the possibility of applying this method without a time consuming pre-processing step. Random forests can be used ... see more

Successful modeling and prediction depend on effective methods for the extraction of domain-relevant variables.  This paper proposes a methodology for identifying domain-specific terms. The proposed methodology relies on a collection of documents lab... see more

Successful modeling and prediction depend on effective methods for the extraction of domain-relevant variables.  This paper proposes a methodology for identifying domain-specific terms. The proposed methodology relies on a collection of documents lab... see more

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