As a remedy, we suggest feature transforms based on Linear Discriminant Analysis (LDA). Since LDA requires operating both with large and dense matrices, we ...
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Classification of textual documents denotes assigning an unknown document to one of predefined classes. This is a straightforward concept from pattern ...
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This paper proposes a Discriminative Semantic Feature (DSF) method for vector space model based text categorization. The DSF method, which involves two stages, ...
This work points out deficiencies in class discrimination of two popular such methods, Latent Semantic Indexing (LSI) and sequential feature selection ...
May 26, 2018 · I tried to classify text using word or character n-gram discriminative features which means that features appear at least 90% in one class.
Classification of textual documents denotes assigning an unknown document to a predefined class. This is a straightforward concept from pattern recognition or ...
This paper points out that LSI ignores discrimination while concentrating on representation. Furthermore, selection methods fail to produce a feature set that ...
We point out deficiencies in class discrimination of two popular such methods, Latent Semantic Indexing (LSI), and sequential feature selection according to ...
To further explore this issue, this paper proposes a novel feature selection method that first selects features in documents with discriminative power and then ...
This paper points out that LSI ignores discrimination while concentrating on representation. Furthermore, selection methods fail to produce a feature set that ...