Title :
Notice of Retraction
An Improved Genetic Algorithm for Text Feature Selection
Author :
Wei Zhao ; Yafei Wang
Author_Institution :
Coll. of Inf. Technol., Jilin Agric. Univ., Changchun, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
High-dimensional feature space affects the quality and efficiency of text categorization. This paper investigates an improved genetic algorithm that how to help select relevant features in text classification. We follow the so-called "region growing" method to initialize the population, and uses k-means algorithm to selection operation to control the scope of the search, ensure the validity of each gene and the speed of convergence. Our experimental results show that our algorithm is quite useful in reduce the high feature dimension, and improved accuracy and efficiency for text classification.
Keywords :
feature extraction; genetic algorithms; pattern classification; pattern clustering; text analysis; improved genetic algorithm; k-means algorithm; region growing method; text classification; text feature selection; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Encoding; Genetics; Heuristic algorithms; Text categorization; feature selection; genetic algorithm; k-means algorithm; text categorization;
Conference_Titel :
Intelligent Computing and Cognitive Informatics (ICICCI), 2010 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-6640-5
DOI :
10.1109/ICICCI.2010.129
