Comparing PCA to information gain as a feature selection method for Influenza-A classification

Authors

Nemin Shaltout, American University in Cairo
Mohamed Moustafa, American University in CairoFollow
Ahmed Rafea, American University in CairoFollow
Ahmed Moustafa, American University in CairoFollow
Mohamed El Hefnawi, National Research Centre

Files

Department

Computer Science & Engineering Department

Abstract

[abstract not available]

Publication Date

3-22-2016

Document Type

Book Chapter

Book Title

ICIIBMS 2015 - International Conference on Intelligent Informatics and Biomedical Sciences

ISBN

SCOPUS_ID:84966539284

Publisher

IEEE

City

Okinawa, Japan

First Page

279

Last Page

283

Keywords

antiviral-resistance classification, bioinformatics, feature selection, Influenza-A, information gain, machine learning, neural networks, PCA

Recommended Citation

APA Citation

Shaltout, N. Moustafa, M. Rafea, A. Moustafa, A. & El Hefnawi, M. (2016).Comparing PCA to information gain as a feature selection method for Influenza-A classification. IEEE. , 279-283
https://fount.aucegypt.edu/faculty_book_chapters/373

MLA Citation

Shaltout, Nemin, et al. Comparing PCA to information gain as a feature selection method for Influenza-A classification. IEEE, 2016.pp. 279-283
https://fount.aucegypt.edu/faculty_book_chapters/373