Karakaya, G. Et Al. 2016. Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach. IEEE TRANSACTIONS ON CYBERNETICS , vol.46, no.6 , 1424-1437.

Karakaya, G., GALELLİ, S., AHİPAŞAOĞLU, S. D., & TAORMİNA, R., (2016). Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach. IEEE TRANSACTIONS ON CYBERNETICS , vol.46, no.6, 1424-1437.

Karakaya, GÜLŞAH Et Al. "Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach," IEEE TRANSACTIONS ON CYBERNETICS , vol.46, no.6, 1424-1437, 2016

Karakaya, GÜLŞAH Et Al. "Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach." IEEE TRANSACTIONS ON CYBERNETICS , vol.46, no.6, pp.1424-1437, 2016

Karakaya, G. Et Al. (2016) . "Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach." IEEE TRANSACTIONS ON CYBERNETICS , vol.46, no.6, pp.1424-1437.

@article{article, author={GÜLŞAH KARAKAYA Et Al. }, title={Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach}, journal={IEEE TRANSACTIONS ON CYBERNETICS}, year=2016, pages={1424-1437} }