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Document classification has received extensive attention in the past decade due to its wide range applications. To efficiently deal with this problem, a novel document classification algorithm is proposed by using marginal fisher analysis (MFA) and minimax probability machine(MPM). Experimental results on the WebKB data set show that the proposed algorithm achieves much better performance than other...
To efficiently deal with spam mail filtering problem, a novel spam filtering algorithm based on locality pursuit projection (LPP) and least square version of SVM(LS-SVM) is proposed in this paper. The mail message features are first extracted by the LPP algorithm, then the LS-SVM classifier is used to classify mails into spam and legitimate. Experimental results demonstrate that the proposed algorithm...
Document categorization is one of the most crucial techniques to assign the documents of a corpus to a set of previously fixed categories. To efficiently deal with document categorization problem, an efficient document categorization algorithm based on local discriminant embedding (LDE) and memetic algorithm (MA) is proposed in this paper. Extensive experiments on Reuter-21578 demonstrate that the...
With the popularization of the Internet, it is challenging to develop spam filters that can effectively eliminate the increasing volumes of unwanted mails automatically before they enter a user's mailbox. To efficiently solve the spam filtering problems, a spam mail filtering method based on neighborhood preserving embedding (NPE) and support vector machines (SVM) classifier is proposed in this paper...
With the explosive growth of World Wide Web, it is of great importance to develop methods for the automatic classifying of large collections of documents. To efficiently tackle this problem, a novel document classification algorithm based on locality pursuit projection (LPP) and SVM is proposed in this paper. The high-dimensional document space are first mapped into lower-dimensional space with LPP,...
To efficiently deal with Web document classification problem, a novel document classification algorithm based on shuffled frog leaping (SFL) algorithm is proposed in this paper. The SFL algorithm combines the benefits of the genetic-based memetic algorithms and the social behavior-based particle swarm optimization algorithms. The experimental results indicate that the proposed SFL algorithm yields...
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