Results 281 to 290 of about 3,113,449 (308)

Multi-label Rule Learning

2022
Forschung im Bereich der Multi-label Klassifizierung beschäftigt sich mit der Entwicklung und Bewertung von Algorithmen, die Vorhersagemodelle für die automatische Zuweisung von Datenpunkten zu einer Untermenge vordefinierter Klassen lernen. Dies unterscheidet sich von traditionellen Problemstellungen, die es nicht erlauben, einzelne Datenpunkte mehr ...
openaire   +2 more sources

ML-FOREST: A Multi-Label Tree Ensemble Method for Multi-Label Classification

IEEE Transactions on Knowledge and Data Engineering, 2016
Multi-label classification deals with the problem where each example is associated with multiple class labels. Since the labels are often dependent to other labels, exploiting label dependencies can significantly improve the multi-label classification performance.
Qingyao Wu, Mingkui Tan, Hengjie Song, Jian Chen 0011, Michael K. Ng 0001   +4 more
openaire   +1 more source

Multi-label learning with multi-label smoothing regularization for vehicle re-identification

Neurocomputing, 2019
This work was supported in part by the National Natural Science Foundation of China under the grants 61871434, 61602191, and 61802136, in part by the Natural Science Foundation of Fujian Province under the grants 2019J06017, 2016J01308 and 2017J05103, in part by the Fujian-100 Talented People Program, in part by High-level Talent Innovation Program of ...
Jinhui Hou, Huanqiang Zeng, Lei Cai, Jianqing Zhu, Jing Chen 0001, Kai-Kuang Ma   +5 more
openaire   +2 more sources

Induction in Multi-Label Domains

2017
All the techniques discussed in the previous chapters assumed that each example is labeled with one and only one class. In realistic applications, however, this is not always the case. Quite often, an example is known to belong to two or more classes at the same time, sometimes to many classes.
openaire   +1 more source

Multi-label Classification without the Multi-label Cost

Proceedings of the 2010 SIAM International Conference on Data Mining, 2010
Xiatian Zhang, Quan Yuan, Shiwan Zhao, Wei Fan, Wentao Zheng, Zhong Wang   +5 more
openaire   +1 more source

A survey on multi-label feature selection from perspectives of label fusion

Information Fusion, 2023
Weiping Ding, Wenbin Qian, Jintao Huang   +2 more
exaly  

Multi-label sampling based on local label imbalance

Pattern Recognition, 2022
Bin Liu, Grigorios Tsoumakas, Konstantinos Blekas   +2 more
exaly  

Multi-label feature selection considering label supplementation

Pattern Recognition, 2021
Wanfu Gao
exaly  

A review of methods for imbalanced multi-label classification

Pattern Recognition, 2021
Adane Nega Tarekegn, Mario Giacobini, Krzysztof Michalak   +2 more
exaly  

The Emerging Trends of Multi-Label Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Ivor Tsang, Xiaobo Shen, Haobo Wang
exaly