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Structural feature selection for wrapper methods. [PDF]

, 2005
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Prediction of hepatitis prognosis using Support Vector Machines and Wrapper Method

2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010
Hepatitis patients are those who need continuous special medical treatment to reduce mortality rate. Using clinical test findings data and machine learning technology such as Support Vector Machines (SVM), the classification and prediction of their life prognosis can be done.
A. H. Roslina, A. Noraziah
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Margin-based wrapper methods for gene identification using microarray

Neurocomputing, 2006
Abstract The gene expression data obtained from microarrays have shown useful in cancer classification problems. DNA microarray data have extremely high dimensionality compared with the small number of available samples. An important step in microarray studies is to select a small number of features (genes) for cancer classifications.
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A Penalized Wrapper Method for Screening Main Effects and Interactions in Supersaturated Designs

Quality and Reliability Engineering International, 2014
Supersaturated designs (SSDs) are defined as fractional factorial designs whose experimental run size is smaller than the number of main effects to be estimated. The main goal using the class of SSDs is to identify the important effects efficiently, that is, at a minimal computational cost and time. Several methods for analyzing SSDs have been proposed
Christos Koukouvinos, Christina Parpoula
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Wrapper Methods for Inductive Learning: Example Application to Bridge Decks

Journal of Computing in Civil Engineering, 2003
The decision tree algorithm is one of the most common techniques of inductive learning. This paper investigates the use of wrapper methods for bagging, boosting, and feature selection to improve the prediction accuracy of the decision tree algorithm. A set of concrete bridge decks is extracted from the Kansas bridge database, and the deterioration of ...
Hani G. Melhem, Yousheng Cheng, Deb Kossler, Dan Scherschligt   +3 more
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A novel relation aware wrapper method for feature selection

Pattern Recognition, 2023
Zhaogeng Liu, Jielong Yang, Li Wang, Yi Chang 0001   +3 more
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Multiple Wrappers Information Extraction Method Based on Tree Model

2009 First International Conference on Information Science and Engineering, 2009
Previous wrappers of information extraction are mostly set for the web page which has one information block, so they are unable to deal with the multiple information blocks web page. Because of the adapt ability of the above mentioned shortcomings, this paper proposes a multiple wrappers information extraction method based on tree model.
Hongguang Suo, Lin Feng, Yong Zhang
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An Improved Version of the Wrapper Feature Selection Method Based on Functional Decomposition

2007
This paper describes an improved version of a previously developed ANOVA and Functional Networks Feature Selection method. This wrapper feature selection method is based on a functional decomposition that grows exponentially as the number of features increases.
Noelia Sánchez-Maroño, Amparo Alonso-Betanzos, Beatriz Pérez-Sánchez   +2 more
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A Wrapper Feature Selection Method for Combined Tree-based Classifiers

2006
The aim of feature selection is to find the subset of features that maximizes the classifier performance. Recently, we have proposed a correlation-based feature selection method for the classifier ensembles based on Hellwig heuristic (CFSH).
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An Evaluation of Filter and Wrapper Methods for Feature Selection in Categorical Clustering

2005
Feature selection for clustering is a problem rarely addressed in the literature. Although recently there has been some work on the area, there is a lack of extensive empirical evaluation to assess the potential of each method. In this paper, we propose a new implementation of a wrapper and adapt an existing filter method to perform experiments over ...
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