Method nave bayes decision tree c45 k nearest

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Unformatted text preview: cation: Kernels that imply a high dimensional feature space show slightly better results in terms of precision and recall, but they are subject to overfitting (Leopold & Kindermann 2002). 3.1.6 Classifier Evaluations During the last years text classifiers have been evaluated on a number of benchmark document collections. It turns out that the level of performance of course depends on the document collection. Table 1 gives some representative results achieved for the Reuters 20 newsgroups collection (Sebastiani 2002, p.38). Concerning the relative quality of classifiers boosted trees, SVMs, and k-nearest neighbors usually deliver top-notch performance, while naïve Bayes and decision trees are less reliable. Method naïve Bayes decision tree C4.5 k-nearest neighbor SVM boosted tree F1 -value 0.795 0.794 0.856 0.870 0.878 Table 1: Performance of Different Classifiers for the Reuters collection 3.2 Clustering Clustering method can be used in order to find groups of documents with similar content. The result of clustering is typically a p...
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