… a comprehensive review on feature selection techniques for text classification. We begin
by … measures used in text classification. Then, we review the most popular text classifiers, …

… In text domains, effective feature selection is essential to make the learning task … feature
selection methods (eg Information Gain) evaluated on a benchmark of 229 text classification …

… learning for text classification. As traditional architecture is more dependent … feature
engineering activities, the selection of features has an important role in improving the classification …

… feature selection is commonly used in text classification to reduce the dimensionality of feature
… Furthermore, we will explore feature selection metrics for high skewed datasets and text …

… feature selection for text classification both theoretically and empirically. Our main result is
an unsupervised feature selection … power of the resultant classification function f with respect …

… number of filter feature selection methods for text classification. Over 100 variants of five
major feature selection criteria were examined using four well-known classification algorithms: a …

… classification. This study proposes a novel filter based probabilistic feature selection method,
namely distinguishing feature selector (DFS), for text classification. The proposed method is …

… In addition to the proposal of new metrics, feature selection studies for text classification
proceed with improvement of current feature selection methods and developing ensemble …

… Text classification is a typical example of this situation, where the size of the initial feature …
the literature offering different feature selection strategies for text classification, mostly focused …

… feature selection algorithms for text classification due to their favourable characteristics of
performing better than traditional-based feature selection … -based feature selection methods, …