@inproceedings{83f53fff079f414a85c81b4c48f42f13,
title = "Enhanced COOT optimization algorithm for Dimensionality Reduction",
abstract = "COOT algorithm is a recent metaheuristic algorithm that simulates American coot birds when moving in the sea. However, the COOT algorithm like other metaheuristic techniques may be stuck in local regions. In this study, a modified COOT algorithm called (mCOOT) is presented which is based on 2 techniques: Opposition-based Learning (OBL) \& Orthogonal Learning to overcome these limitations. Moreover, to test the novel algorithm called mCOOT, we apply it to the dimensionality reduction problem using 9 UCI datasets and compare it with the original algorithm and 3 other ones. Results prove the effectivness and superiority of the proposed algorithm in solving feature selection in terms of classification accuracy and selected features numbers.",
keywords = "COOT, Dimensionality Reduction, Feature Selection, mCOOT",
author = "Mostafa, \{Reham R.\} and Hussien, \{Abdelazim G.\} and Khan, \{Muhammad Attique\} and Seifedine Kadry and Hashim, \{Fatma A.\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th International Conference of Women in Data Science at Prince Sultan University, WiDS-PSU 2022 ; Conference date: 28-03-2022 Through 29-03-2022",
year = "2022",
doi = "10.1109/WiDS-PSU54548.2022.00020",
language = "English",
series = "Proceedings - 2022 5th International Conference of Women in Data Science at Prince Sultan University, WiDS-PSU 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "43--48",
editor = "Tanzila Saba and Jamail, \{Nor Shahida\} and Rabia Latif and Rehman Khan",
booktitle = "Proceedings - 2022 5th International Conference of Women in Data Science at Prince Sultan University, WiDS-PSU 2022",
address = "United States",
}