  As an emerging research direction, online streaming feature selection deals
with sequentially added dimensions in a feature space while the number of data
instances is fixed. Online streaming feature selection provides a new,
complementary algorithmic methodology to enrich online feature selection,
especially targets to high dimensionality in big data analytics. This paper
introduces the first comprehensive open-source library for use in MATLAB that
implements the state-of-the-art algorithms of online streaming feature
selection. The library is designed to facilitate the development of new
algorithms in this exciting research direction and make comparisons between the
new methods and existing ones available.
