Hybrid Feature Selection
Hybrid Feature Selection is a feature selection strategy that combines multiple distinct paradigms—such as filter, wrapper, and embedded methods—within a unified framework to leverage their complementary strengths in identifying optimal feature subsets.
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2017–2026
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Normalized Mutual Information Feature Selection
P. A. Estévez, M. Tesmer, Carlos A. Perez et al. · IEEE Transactions on Neural Networks · 2009 · 1.3K citations · Full text
Sentiment analysis in multiple languages
Ahmed Abbasi, Hsinchun Chen, Arab Salem · ACM Transactions on Information Systems · 2008 · 894 citations
Computing, Arabic, Computer Science +17
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Mansoura University
Al Mansurah, Egypt
15 h-index
29 publications
2.6K citations

Jadavpur University
Kolkata, India
14 h-index
48 publications
2.4K citations

Benha University
Banhā, Egypt
12 h-index
16 publications
1.1K citations
National University of Sciences and Technology
Islamabad, Pakistan
11 h-index
21 publications
801 citations

Deakin University
Burwood, Australia
11 h-index
21 publications
1.5K citations

University of Tehran
Tehran, Iran
11 h-index
16 publications
890 citations
Vellore Institute of Technology University
Vellore, India
11 h-index
20 publications
4.5K citations
National Institute of Technology Raipur
Raipur, India
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26 publications
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