Results 61 to 70 of about 881,675 (221)

Application of Label Correlation in Multi-Label Classification: A Survey

Applied Sciences
Multi-Label Classification refers to the classification task where a data sample is associated with multiple labels simultaneously, which is widely used in text classification, image classification, and other fields. Different from the traditional single-
Shan Huang, Wenlong Hu, Bin Lu, Qiang Fan, Xinyao Xu, Xiaolei Zhou, Hao Yan   +6 more
doaj   +1 more source

A Novel IGBT Health Evaluation Method Based on Multi-Label Classification

IEEE Access, 2019
The IGBT health evaluation of power semiconductor devices is usually based on the threshold evaluation method, which is usually a single characteristic parameter evaluation system. This kind of evaluation method cannot reflect the internal correlation of
Ruikun Quan, Hui Li, Yaogang Hu, Pei Gao
doaj   +1 more source

Multi-Label Remote Sensing Image Land Cover Classification Based on a Multi-Dimensional Attention Mechanism

Remote Sensing, 2023
For the multi-label classification task of remote sensing images (RSIs), it is difficult to accurately extract feature information from complex land covers, and it is easy to generate redundant features by ordinary convolution extraction features.
Haihui You, Juntao Gu, Weipeng Jing
doaj   +1 more source

Application of deep and machine learning techniques for multi-label classification performance on psychotic disorder diseases

Informatics in Medicine Unlocked, 2021
Electronic Health Records (EHRs) hold symptoms of many diverse diseases and it is imperative to build models to recognise these problems early and classify the diseases appropriately. This classification task could be presented as a single or multi-label
Israel Elujide, S. Fashoto, B. Fashoto, Elliot Mbunge, S. Folorunso, Jeremiah O. Olamijuwon   +5 more
semanticscholar   +1 more source

A Novel Progressive Multi-label Classifier for Classincremental Data

, 2016
In this paper, a progressive learning algorithm for multi-label classification to learn new labels while retaining the knowledge of previous labels is designed.
Dave, Mihika, Er, Meng Joo, Tapiawala, Sahil, Venkatesan, Rajasekar   +3 more
core   +1 more source

Reliable Multi-label Classification: Prediction with Partial Abstention

, 2020
In contrast to conventional (single-label) classification, the setting of multilabel classification (MLC) allows an instance to belong to several classes simultaneously.
Hüllermeier, Eyke, Nguyen, Vu-Linh
core   +1 more source

HamNava: A Dataset for Multi‑Label Instrument Classification

Transactions of the International Society for Music Information Retrieval
Despite significant advancements in music information retrieval, much of the progress has focused on musical traditions rooted in Western cultures. One of the hindrances preventing researchers from delving further into other musical traditions is the ...
Pouya Mohseni, Bagher BabaAli, Hooman Asadi   +2 more
doaj   +1 more source

Extreme Learning Machine for Multi-Label Classification

Entropy, 2016
Extreme learning machine (ELM) techniques have received considerable attention in the computational intelligence and machine learning communities because of the significantly low computational time required for training new classifiers.
Xia Sun, Jingting Xu, Changmeng Jiang, Jun Feng, Su-Shing Chen, Feijuan He   +5 more
doaj   +1 more source

Efficient multi-label classification for evolving data streams [PDF]

, 2010
Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios.
Bifet, Albert, Holmes, Geoffrey, Pfahringer, Bernhard, Read, Jesse   +3 more
core   +1 more source

Towards Explainable Multi-Label Classification

2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), 2019
Multi-label classification is a very active research area and many real-world applications need efficient multi-label learning. During recent years, explaining machine learning predictions is also a very hot topic. A lot of approaches have been proposed for explaining multi-class classifier predictions.
openaire   +2 more sources