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In the last decade spam detection has been addressed as a text classification or categorization problem. In this paper we propose a new dynamic weighted voting method based on the combination of clustering and weighted voting, and apply it to the task of spam filtering. In order to classify a new sample, it first compares with all cluster centroids and its similarity to each cluster is identified;...
This work systematically examines a Clustering Inside Classes (CIC) approach to classification. In CIC, each class is partitioned into subclasses based on cluster analysis. We find that CIC, by extracting local structure and producing compact subclasses, can improve performance of linear classifiers such as SVM and logistic regression. It is compared against a global classifier on four benchmark datasets...
This paper presents a new algorithm of Web page classification, CUCS(Combined UC and SVM), for large training set. CUCS combines the advantages of SVM (Support Vector Machine) and UC (Unsupervised Clustering), achieving high precision and fast speed. In the training stage, CUCS gets clustering centers, which include positive example centers and negative ones, by means of UC. Then CUCS prunes training...
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