… All in all, there are many types of feature selection methods exist in the … text classifiers using
most widely used feature selection methods. Further, we evaluated the feature selection (FS) …

… This paper proposes three feature selection algorithms with feature weight scheme and …
for the text document clustering problem. Text document clustering is a new trend in text mining; …

… of document length. For instance, by merging two copies of a particular text document d to
generate a pseudo-document 'd … be carried out among two documents. When fed with another …

… a higher number of features. To overcome this problem, we propose a novel Variable Global
Feature Selection Scheme (VGFSS) to select a variable number of features from each class …

… scoring measures that we experimentally compared including known measures that were
already used for feature selection in text domains and some new measures we propose here. …

… Feature selection on multi-label documents for automatic text … This paper presents a
systematic document transformation … text collections, we show that the choice of document …

… text documents, in this paper we introduce two novel feature selection methods for text …
feature by its overall contribution to the documents similarity in a dataset. Another is Iterative …

… In Section 2 we present our μ-document-based approach to feature selection, and we briefly
describe (in Section 2.2) the four feature selection methods for ordinal text classification that …

… terms between the documents of the training corpus. Supervised feature selection using
χ2 … Forman [11] shows a comparative study of twelve feature selection methods on 229 text …

… We apply feature selection to documents in the preprocessing of kNN and LLSF. The e
ectiveness of a feature selection method is evaluated using the performance of kNN and LLSF on …