HIBoost: A hubness-aware ensemble learning algorithm for high-dimensional imbalanced data classification

2020 ◽  
Vol 39 (1) ◽  
pp. 133-144
Author(s):  
Qin Wu ◽  
Yaping Lin ◽  
Tuanfei Zhu ◽  
Yue Zhang
Keyword(s):  
Ensemble Learning ◽  
Learning Algorithm ◽  
Imbalanced Data ◽  
Data Classification ◽  
High Dimensional ◽  
Imbalanced Data Classification ◽  
Ensemble Learning Algorithm

scholarly journals Rough set based ensemble learning algorithm for agricultural data classification

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1917-1930 ◽  
Author(s):  
Lei Shi ◽  
Qiguo Duan ◽  
Juanjuan Zhang ◽  
Lei Xi ◽  
Hongbo Qiao ◽  
...  
Keyword(s):  
Ensemble Learning ◽  
Rough Set ◽  
Rough Set Theory ◽  
Learning Algorithm ◽  
Uncertain Data ◽  
Data Classification ◽  
Research Area ◽  
Experimental Comparison ◽  
Classification Problems ◽  
Ensemble Learning Algorithm

Agricultural data classification attracts more and more attention in the research area of intelligent agriculture. As a kind of important machine learning methods, ensemble learning uses multiple base classifiers to deal with classification problems. The rough set theory is a powerful mathematical approach to process unclear and uncertain data. In this paper, a rough set based ensemble learning algorithm is proposed to classify the agricultural data effectively and efficiently. An experimental comparison of different algorithms is conducted on four agricultural datasets. The results of experiment indicate that the proposed algorithm improves performance obviously.

A synthetic neighborhood generation based ensemble learning for the imbalanced data classification

2017 ◽  
Vol 48 (8) ◽  
pp. 2441-2457 ◽  
Author(s):  
Zhi Chen ◽  
Tao Lin ◽  
Xin Xia ◽  
Hongyan Xu ◽  
Sha Ding
Keyword(s):  
Ensemble Learning ◽  
Imbalanced Data ◽  
Data Classification ◽  
Imbalanced Data Classification
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