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Please use this identifier to cite or link to this item: http://hdl.handle.net/2262/12581

Title: Feature Extraction for Classification in Knowledge
Author: Tsymbal, Alexey
Sponsor: Science Foundation Ireland
Keywords: Computer Science
Issue Date: 2003
Publisher: Trinity College Dublin, Department of Computer Science
Citation: Tsymbal, Alexey. 'Feature Extraction for Classification in Knowledge'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-2003-32, 2003, pp7
Series/Report no.: Computer Science Technical Report
TCD-CS-2003-32
Abstract: Dimensionality reduction is a very important step in the data mining process. In this paper, we consider feature extraction for classification tasks as a technique to overcome problems occurring because of “the curse of dimensionality”. We consider three different eigenvector-based feature extraction approaches for classification. The summary of obtained results concerning the accuracy of classification schemes is presented and the issue of search for the most appropriate feature extraction method for a given data set is considered. A decision support system to aid in the integration of the feature extraction and classification processes is proposed. The goals and requirements set for the decision support system and its basic structure are defined. The means of knowledge acquisition needed to build up the proposed system are considered.
URI: https://www.cs.tcd.ie/publications/tech-reports/reports.03/TCD-CS-2003-32.pdf
http://hdl.handle.net/2262/12581
Appears in Collections:Computer Science Technical Reports

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