Comparative Study on Fast Feature Selection
Abstract
No one can deny how feature selection became an important aspect of the machine learning field. Feature selection has proved its ability to overcome the problem that known as the curse of dimensionality, which raises when a number of features for a given data is large and required to be expressed in a space of high dimensions. In this paper, we are going to investigate the algorithms in feature selection as well as the enhanced ones in the acceleration of the feature selection process. We have shown the algorithms, their limitations, and how authors have enhanced them.Downloads
Published
2018-08-08
Issue
Section
Articles
License
Authors submitting articles to the IJITLS warrent that the work is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY 4.0).
By submitting an article, the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.