Results 101 to 110 of about 881,675 (221)
Multi-label Lazy Associative Classification [PDF]
, 2007 Most current work on classification has been focused on learning from a set of instances that are associated with a single label (i.e., single-label classification). However, many applications, such as gene functional prediction and text categorization, may allow the instances to be associated with multiple labels simultaneously.
Adriano Veloso +3 more
openaire +1 more source
A Survey of Multi-Label Text Classification Under Few-Shot Scenarios
Applied SciencesMulti-label text classification is a fundamental and important task in natural language processing, with widespread applications in specialized domains such as sentiment analysis, legal document classification, and medical coding.
Wenlong Hu +5 more
doaj +1 more source
Hierarchical multi-label news article classification with distributed semantic model based features
IJAIN (International Journal of Advances in Intelligent Informatics), 2019 Automatic news categorization is essential to automatically handle the classification of multi-label news articles in online portal. This research employs some potential methods to improve performance of hierarchical multi-label classifier for Indonesian
Ivana Clairine Irsan +1 more
doaj +1 more source
Open Vocabulary Multi-label Video Classification
Accepted at ECCV ...
Rohit Gupta +7 more
openaire +2 more sources
Multi-Label Classification of Remote Sensing Images with Mixed Noise [PDF]
Jisuanji gongchengRemote sensing images usually contain multiple land features and semantic information. Using multi-label learning methods to classify remote sensing images can improve the understanding of image semantics.
OU Hanzhi, HUANG Rui
doaj +1 more source
IEEE Access, 2018 To solve the problem that traditional multi-label support vector machine (SVM) classification algorithm adopting nonlinear kernel has been severely restricted from being used on large-scale data sets, we propose fast multi-label low-rank-linearized SVM ...
Zhongwei Sun +4 more
doaj +1 more source
Multi-label Text Classification by Fusing Pseudo-label Generation and Data Augmentation
Journal of Harbin University of Science and TechnologyAiming at the problem that the multi-label text classification algorithm ignores the noise label and lacks the combination incentive of true and false, which leads to the weak robustness of the model and the poor classification effect, a cascaded BiLSTM-
WANG Shuitao +5 more
doaj +1 more source
Pre-training of Heterogeneous Graph Neural Networks for Multi-label Document Classification [PDF]
Jisuanji kexueMulti-label document classification aims to associate document instances with relevant labels,which has received increasing research attention in recent years.Existing multi-label document classification methods attempt to explore the fusion of ...
WU Jiawei, FANG Quan, HU Jun, QIAN Shengsheng
doaj +1 more source
Nearest Labelset Using Double Distances for Multi-label Classification
, 2017 Multi-label classification is a type of supervised learning where an instance may belong to multiple labels simultaneously. Predicting each label independently has been criticized for not exploiting any correlation between labels.
Gweon, Hyukjun +2 more
core
Applications of Multi-Label Classification
International Journal of Innovative Technology and Exploring Engineering, 2020 The absence of labels and the bad quality of data is a prevailing challenge in numerous data mining and machine learning problems. The performance of a model is limited by available data samples with few labels for training. These problems are ultra-critical in multi-label classification, which usually needs clean data.
openaire +1 more source