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pro vyhledávání: '"Temraz, Mohammed"'
Autor:
Temraz, Mohammed, Keane, Mark T.
Learning from class imbalanced datasets poses challenges for many machine learning algorithms. Many real-world domains are, by definition, class imbalanced by virtue of having a majority class that naturally has many more instances than its minority
Externí odkaz:
http://arxiv.org/abs/2111.03516
Publikováno v:
IJCAI-21 Workshop on DL-CBR-AML, July 2021
Recently, it has been proposed that fruitful synergies may exist between Deep Learning (DL) and Case Based Reasoning (CBR); that there are insights to be gained by applying CBR ideas to problems in DL (what could be called DeepCBR). In this paper, we
Externí odkaz:
http://arxiv.org/abs/2104.14461
Autor:
Temraz, Mohammed, Kenny, Eoin, Ruelle, Elodie, Shalloo, Laurence, Smyth, Barry, Keane, Mark T
Climate change poses a major challenge to humanity, especially in its impact on agriculture, a challenge that a responsible AI should meet. In this paper, we examine a CBR system (PBI-CBR) designed to aid sustainable dairy farming by supporting grass
Externí odkaz:
http://arxiv.org/abs/2104.04008
Autor:
Temraz, Mohammed, Keane, Mark T.
Publikováno v:
In Machine Learning with Applications 15 September 2022 9
