Feature Selection Methods for Linked Data: Limitations, Capabilities and Potentials

Author:

Cherrington Marianne1,Airehrour David2,Lu Joan3,Xu Qiang3,Wade Stephen3,Madanian Samaneh4

Affiliation:

1. University of Huddersfield, Auckland, New Zealand

2. Unitec Institute of Technology, Auckland, New Zealand

3. University of Huddersfield, Huddersfield, United Kingdom

4. Auckland University of Technology, Auckland, New Zealand

Publisher

ACM Press

Reference93 articles.

1. Saeys Y, Inza I, Larrañaga P. A review of feature selection techniques in bioinformatics. Bioinformatics. Oct 1; 23(19):2507--17, (2017).

2. Tang J, Liu H. An unsupervised feature selection framework for social media data. IEEE Transactions on Knowledge and Data Engineering. Dec 1; 26(12):2914--27, (2014).

3. Thabtah F. An accessible and efficient autism screening method for behavioural data and predictive analyses. Health informatics journal. Sep 19:1460458218796636, (2018).

4. Qabajeh I, Thabtah F, Chiclana F. A recent review of conventional vs. automated cybersecurity anti-phishing techniques. Computer Science Review. Aug 31; 29:44--55, (2018).

5. Hastie T, Tibshirani R, Friedman J. The elements of statistical learning: data mining, inference, and prediction, Springer Series in Statistics, (2009): xxii-745.

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1. Feature Selection on Linked Data: A Review;Algorithms for Intelligent Systems;2021

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