Results 91 to 100 of about 881,675 (221)

Boosting-based Multi-label Classification [PDF]

, 2013
JUCS - Journal of Universal Computer Science Volume Nr.
Kajdanowicz,Tomasz, Kazienko,Przemyslaw
openaire   +1 more source

Multi-label Classification: a survey

International Journal of Engineering & Technology, 2018
Wide use of internet generates huge data which needs proper organization leading to text categorization. Earlier it was found that a document describes one category. Soon it was realized that it can describe multiple categories simultaneously. This scenario reveals the use of multi-label classification, a supervised learning approach, which assigns a ...
Vaishali S. Tidake, Shirish S. Sane
openaire   +2 more sources

Multi-Label Classifier Chains for Bird Sound [PDF]

, 2013
Bird sound data collected with unattended microphones for automatic surveys, or mobile devices for citizen science, typically contain multiple simultaneously vocalizing birds of different species.
Briggs, Forrest, Fern, Xiaoli Z., Irvine, Jed   +2 more
core   +1 more source

Multi-Label Confusion Tensor

IEEE Access
The confusion matrix is the tool commonly used for the evaluation of the performance of a classification algorithm. While the computation of the confusion matrix for multi-class classification follows a well-developed procedure, the common approach for ...
Damir Krstinic, Ana Kuzmanic Skelin, Ivan Slapnicar, Maja Braovic   +3 more
doaj   +1 more source

A Multi-Label Image Classification Method based on Label Correlation Learning Network

Taiyuan Ligong Daxue xuebao
[Purposes] To meet the challenges posed by label feature confusions and limitations in label relationships in multi-label image classification tasks, a novel approach to multi-label image classification based on label correlation learning network (MLLCLN)
WANG Lufang, ZHANG Haiyun
doaj   +1 more source

Multi-Label Image Classification by Feature Attention Network

IEEE Access, 2019
Learning the correlation among labels is a standing-problem in the multi-label image recognition task. The label correlation is the key to solve the multi-label classification but it is too abstract to model.
Zheng Yan, Weiwei Liu, Shiping Wen, Yin Yang   +3 more
doaj   +1 more source

Data scarcity, robustness and extreme multi-label classification

Machine-mediated learning, 2019
The goal in extreme multi-label classification (XMC) is to learn a classifier which can assign a small subset of relevant labels to an instance from an extremely large set of target labels.
Rohit Babbar, B. Scholkopf
semanticscholar   +1 more source

A Multi-Label Text Categorization Algorithm Incorporating Label-Guided Attention Mechanisms

IEEE Access
This paper proposes a multi-label text classification algorithm based on causal relationships to address the current challenge of accurately capturing label correlations in multi-label text classification tasks. The algorithm comprises a basic prediction
Shaocong Guo, Qian Hao
doaj   +1 more source

KFHE-HOMER: A multi-label ensemble classification algorithm exploiting sensor fusion properties of the Kalman filter

, 2019
Multi-label classification allows a datapoint to be labelled with more than one class at the same time. In spite of their success in multi-class classification problems, ensemble methods based on approaches other than bagging have not been widely ...
Mac Namee, Brian, Pakrashi, Arjun
core  

Classification in Multi-Label Datasets

, 2023
Multi-label datasets contain several classes, where each class can have multiple values. They appear in several domains such as music categorization into emotions and directed marketing. In this chapter, we are interested in the most popular task of Data Mining, which is the classification, more precisely classification in multi-label datasets.
openaire   +2 more sources