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Performance of feature selection methods
- Curr. Genomics
, 2009
"... Abstract: High-throughput biological technologies offer the promise of finding feature sets to serve as biomarkers for medical applications; however, the sheer number of potential features (genes, proteins, etc.) means that there needs to be massive feature selection, far greater than that envisione ..."
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Cited by 2 (1 self)
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Abstract: High-throughput biological technologies offer the promise of finding feature sets to serve as biomarkers for medical applications; however, the sheer number of potential features (genes, proteins, etc.) means that there needs to be massive feature selection, far greater than
COMBINING MULTIPLE FEATURE SELECTION METHODS
"... This paper proposes a feature selection method that combines various feature selection techniques. Feature selection has been realized as one of the most important processes in various applications, especially pattern classification problems. When too many attributes are involved, training a machine ..."
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Cited by 1 (0 self)
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This paper proposes a feature selection method that combines various feature selection techniques. Feature selection has been realized as one of the most important processes in various applications, especially pattern classification problems. When too many attributes are involved, training a
A Review of Feature Selection Methods for Classification Problem
"... Abstract — The Classification are carried out using various feature selection technique. The feature selection methods allows the classification to be carried out more accurately and efficiently. Feature selection is one of the leading trends in the research work going on. There are various feature ..."
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Abstract — The Classification are carried out using various feature selection technique. The feature selection methods allows the classification to be carried out more accurately and efficiently. Feature selection is one of the leading trends in the research work going on. There are various feature
An Efficient Feature Selection Method for Arabic Text Classification
"... This paper proposes an efficient, Chi-Square-based, feature selection method for Arabic text classification. In Data Mining, feature selection is a preprocessing step that can improve the classification performance. Although few works have studied the effect of feature selection methods on Arabic te ..."
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This paper proposes an efficient, Chi-Square-based, feature selection method for Arabic text classification. In Data Mining, feature selection is a preprocessing step that can improve the classification performance. Although few works have studied the effect of feature selection methods on Arabic
FEATURE SELECTION METHODS FOR SOFTCOMPUTING CLASSIFICATION
"... ABSTRACT: Feature selection and feature creating are two of the most important and difficult tasks in the field of pattern recognition. It involves determining a good feature subset given a set of candidate features. The acoustic analysis of vibration signals in the time and frequency domain frequen ..."
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frequently generates a large number of features and makes a reduction of dimensionality necessary. The present method is an approach to improve pattern classifier performance using a feature selection process. For this task the two parts feature selection and the inherent classification step are combined
A Review on Feature Selection Methods For Classification Tasks
, 2016
"... Abstract: In recent years, application of feature selection methods in medical datasets has greatly increased. The challenging task in feature selection is how to obtain an optimal subset of relevant and non redundant features which will give an optimal solution without increasing the complexity of ..."
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Abstract: In recent years, application of feature selection methods in medical datasets has greatly increased. The challenging task in feature selection is how to obtain an optimal subset of relevant and non redundant features which will give an optimal solution without increasing the complexity
Feature selection methods for conversational recommender systems
- In Proceedings of the IEEE International Conference on e-Technology, e-Commerce and e-Services, Hong Kong
, 2005
"... This paper focuses on question selection methods for conversational recommender systems. We consider a scenario, where given an initial user query, the recommender system may ask the user to provide additional features describing the searched products. The objective is to generate questions/features ..."
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Cited by 11 (3 self)
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This paper focuses on question selection methods for conversational recommender systems. We consider a scenario, where given an initial user query, the recommender system may ask the user to provide additional features describing the searched products. The objective is to generate questions/features
Feature Selection Methods for an Improved SVM Classifier
- Proceedings of the 14 th International Conference on Computational and Information Science, pp 83-89, Prague, August 2006 PWASET VOLUME 15 OCTOBER 2006 ISSN 1307-6884 221 © 2006 WASET.ORG
"... Abstract—Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions ..."
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Cited by 2 (0 self)
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can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, three feature selection methods are evaluated: Random Selection, Information Gain (IG) and Support Vector Machine feature selection
An Efficient Feature Selection Method for Object Detection
- Int. Conf. on Advances in Pattern Recognition
, 2005
"... Abstract. We propose a simple yet efficient feature-selection method — based on principle component analysis (PCA) — for SVM-based classifiers. The idea is to select features whose corresponding axes are closest to the principle components computed from a data distribution by PCA. Experimental resu ..."
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Abstract. We propose a simple yet efficient feature-selection method — based on principle component analysis (PCA) — for SVM-based classifiers. The idea is to select features whose corresponding axes are closest to the principle components computed from a data distribution by PCA. Experimental
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