Results 71 to 80 of about 881,675 (221)

Attention-Induced Embedding Imputation for Incomplete Multi-View Partial Multi-Label Classification

AAAI Conference on Artificial Intelligence
As a combination of emerging multi-view learning methods and traditional multi-label classification tasks, multi-view multi-label classification has shown broad application prospects.
Chengliang Liu, Jinlong Jia, Jie Wen, Yabo Liu, Xiaoling Luo, Chao Huang, Yong Xu   +6 more
semanticscholar   +1 more source

An Efficient Multi-Label SVM Classification Algorithm by Combining Approximate Extreme Points Method and Divide-and-Conquer Strategy

IEEE Access, 2020
Excessive time complexity has severely restricted the application of support vector machine (SVM) in large-scale multi-label classification. Thus, this paper proposes an efficient multi-label SVM classification algorithm by combining approximate extreme ...
Zhongwei Sun, Xiuyan Liu, Keyong Hu, Zhuang Li, Jing Liu   +4 more
doaj   +1 more source

Addressing Imbalance Problem for Multi Label Classification of Scholarly Articles

IEEE Access, 2023
Scientific document classification is an important field of machine learning. Currently, scientific document category identification is done manually.
Aiman Hafeez, Tariq Ali, Asif Nawaz, Saif Ur Rehman, Azhar Imran Mudasir, Abdulaziz A. Alsulami, Ali Alqahtani   +6 more
doaj   +1 more source

A new genetic algorithm for multi-label correlation-based feature selection. [PDF]

, 2015
This paper proposes a new Genetic Algorithm for Multi-Label Correlation-Based Feature Selection (GA-ML-CFS). This GA performs a global search in the space of candidate feature subset, in order to select a high-quality feature subset is used by a multi ...
Freitas, Alex A., Jungjit, Suwimol
core  

Learning Interpretable Rules for Multi-label Classification

, 2018
Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels simultaneously.
A Gabriel, AA Freitas, AJ Knobbe, B Liu, B Minnaert, D Malerba, E Gibaja, E Gibaja, E Loza Mencía, E Montañés, F Charte, F Herrera, F Janssen, F Thabtah, G Bosc, G Tsoumakas, Grigorios Tsoumakas, H Allahyari, J Arunadevi, J Demšar, J Fürnkranz, J Han, J Hipp, J Read, JN Sulzmann, K Dembczyński, K Dembczyński, L Chekina, L Raedt De, LE Sucar, M Atzmüller, M Beckerle, M Friedman, M Zhang, Miltiadis Allamanis, MR Boutell, P Kralj Novak, PJ Hayes, R Senge, RM Cameron-Jones, Shantanu Godbole, W Duivesteijn, W Waegeman, WW Cohen   +43 more
core   +1 more source

Deep active learning for multi label text classification

Scientific Reports
Given a set of labels, multi-label text classification (MLTC) aims to assign multiple relevant labels for a text. Recently, deep learning models get inspiring results in MLTC.
Qunbo Wang, Hangu Zhang, Wentao Zhang, Lin Dai, Yu Liang, Haobin Shi   +5 more
doaj   +1 more source

MsCoa: Multi-Step Co-Attention Model for Multi-Label Classification

IEEE Access, 2019
Multi-label text classification (MLC) task, as one of the sub-tasks of natural language processing, has broad application prospects. On the basis of studying the previous research work, this research takes the relationship among text information, leading
Haoyang Ma, Yujun Li, Xianpeng Ji, Junlei Han, Zeqiang Li   +4 more
doaj   +1 more source

A Multi-Label Classification With Hybrid Label-Based Meta-Learning Method in Internet of Things

IEEE Access, 2020
With the widespread adoption of Internet connected devices and the application of Internet of Things (IoT), more and more research efforts focusing on using machine learning techniques in recognizing activities from IoT sensors, especially in solving ...
Sung-Chiang Lin, Chih-Jou Chen, Tsung-Ju Lee   +2 more
doaj   +1 more source

Multi-Label Classification of Fundus Images With EfficientNet

IEEE Access, 2020
Convolutional neural network (CNN) has achieved remarkable success in the field of fundus images due to its powerful feature learning ability. Computer-aided diagnosis can obtain information with reference value for doctors in clinical diagnosis or ...
Jing Wang, Liu Yang, Zhanqiang Huo, Wei He, Junwei Luo   +4 more
semanticscholar   +1 more source

A multi-label classification method for disposing incomplete labeled data and label relevance

Dianxin kexue, 2016
Multi-label classification methods have been applied in many real-world fields，in which the labels may have strong relevance and some of them even are incomplete or missing.However，existing multi-label classification algorithms are unable to handle both ...
Lina ZHANG, Lingpeng DAI, Tai KUANG
doaj   +2 more sources