IF-MCA: Importance Factor-Based Multiple Correspondence Analysis for Multimedia Data Analytics

Multimedia concept detection is a challenging topic due to the well-known class imbalance issue, where the data instances are distributed unevenly across different classes. This problem becomes even more prominent when the minority class that contains an extremely small proportion of the data repres...

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Veröffentlicht in:	IEEE transactions on multimedia 2018-04, Vol.20 (4), p.1024-1032
Hauptverfasser:	Yang, Yimin, Pouyanfar, Samira, Tian, Haiman, Chen, Min, Chen, Shu-Ching, Shyu, Mei-Ling
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Data mining Decision trees Feature extraction feature selection Importance factor information gain Multimedia communication multiple correspondence analysis (MCA) Testing Training
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