ADAPT Funded Investigator Publishes Work on an Unsupervised Algorithm for Selecting Optimal Features from Mixed Datasets

04 October 2022

This paper was published as part of a larger project funded by the Marie Curie Career-FIT programme.

ADAPT Funded Investigator, Dr. Susan McKeever has recently had research published in the open access journal Expert Systems with Applications (ELSEVIER). The research paper titled “A multiple association-based unsupervised feature selection algorithm for mixed data sets” was co-authored by Ayman Taha (Cairo University, Egypt), Ali S.Hadi (American University in Cairo, Egypt and Cornell University, Ithaca, NY, USA) and Bernard Cosgrave (DOCOsoft, Dublin, Ireland).

The work is part of a larger project, funded by the Marie Curie Career-FIT programme, carried out in partnership with Irish insurance software company DocoSoft. The paper proposes a generic multiple association measure for mixed datasets and a novel feature selection algorithm that uses multiple association across features.

Expert Systems With Applications is a refereed international journal whose focus is on exchanging information relating to expert and intelligent systems applied in industry, government, and universities worldwide. 

To read more about this paper, access it here