Feature selection for unsupervised tasks is particularly challenging, especially when dealing with text data. The increase in online documents and email communication creates a nee...
Nirmalie Wiratunga, Robert Lothian, Stewart Massie
Abstract. This paper presents a study of 25 structural features extracted from samples of grapheme `th' that correspond to features commonly used by forensic document examiner...
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
We study an interesting and challenging problem, online streaming feature selection, in which the size of the feature set is unknown, and not all features are available for learni...
Higher order spatial features, such as doublets or
triplets have been used to incorporate spatial information
into the bag-of-local-features model. Due to computational
limits, ...