Results 171 to 180 of about 881,675 (221)

Multi-Label Classification With Label-Specific Feature Generation: A Wrapped Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Label-specific features serve as an effective strategy to learn from multi-label data, where a set of features encoding specific characteristics of each label are generated to help induce multi-label classification model.
Zeping Yu, Min-Ling Zhang
semanticscholar   +1 more source

Multi-objective PSO based online feature selection for multi-label classification

Knowledge-Based Systems, 2021
Feature selection approaches aim to select a set of prominent features that best describe the data to improve the efficiency without degrading the performance of the model.
Dipanjyoti Paul, Anushree Jain, S. Saha, J. Mathew   +3 more
semanticscholar   +1 more source

Active k-labelsets ensemble for multi-label classification

Pattern Recognition, 2021
The random k-labelsets ensemble (RAkEL) is a multi-label learning strategy that integrates many single-label learning models. Each single-label model is constructed using a label powerset (LP) technique based on a randomly generated size-k label subset ...
Ran Wang, S. Kwong, Xu Wang, Yuheng Jia
semanticscholar   +1 more source

MG-GCN: Multi-Granularity Graph Convolutional Neural Network for Multi-Label Classification in Multi-Label Information System

IEEE Transactions on Emerging Topics in Computational Intelligence
Recently, many researchers have applied Graph Convolutional Neural Networks (GCN) to multi-label learning tasks by establishing relations among labels.
Ting Yu, Heng Xie, Mingjie Cai, Weiping Ding   +3 more
semanticscholar   +1 more source

Multi-label Classification: Detailed Analysis

2021
Multi-label classification is a classification problem wherein output domain multiple labels are assigned to each instance. Because of this reason importance of multi-label classification has increased with time. It has applications in almost all fields.
Mathur Swati, Mathur Pratistha
openaire   +1 more source

Hierarchical Multi-label Text Classification

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019
Hierarchical multi-label text classification (HMTC) is a fundamental but challenging task of numerous applications (e.g., patent annotation), where documents are assigned to multiple categories stored in a hierarchical structure. Categories at different levels of a document tend to have dependencies.
Wei Huang, Enhong Chen, Qi Liu, Yuying Chen, Zai Huang, Yang Liu, Zhou Zhao, Dan Zhang, Shijin Wang   +8 more
openaire   +1 more source

Multi-label Connectionist Temporal Classification

2019 International Conference on Document Analysis and Recognition (ICDAR), 2019
The Connectionist Temporal Classification (CTC) loss function [1] enables end-to-end training of a neural network for sequence-to-sequence tasks without the need for prior alignments between the input and output. CTC is traditionally used for training sequential, single-label problems; each element in the sequence has only one class.
Curtis Wigington, Brian Price, Scott Cohen   +2 more
openaire   +1 more source

Multi-label classification of feedbacks

Journal of Intelligent & Fuzzy Systems, 2021
This work deals with educational text mining, a field of natural language processing applied to education. The objective is to classify the feedback generated by teachers in online courses to the activities sent by students according to the model of Hattie and Timperley (2007), considering that feedback may be at the levels task, process, regulation ...
Ruiz Alonso, Dorian, Zepeda Cortés, Claudia, Castillo Zacatelco, Hilda, Carballido Carranza, José Luis, García Cué, José Luis   +4 more
openaire   +1 more source

Multi-Label Associative Classification

2011
A typical assumption in classification is that outputs are mutually exclusive, so that an input can be mapped to only one output (i.e., single-label classification ). However, due to ambiguity or multiplicity, it is quite natural that many applications violate this assumption, allowing inputs to be mapped to multiple outputs simultaneously. Multi-label
Adriano Veloso, Wagner Meira
openaire   +1 more source

Negative Comments Multi-Label Classification

2020 International Conference on Computational Performance Evaluation (ComPE), 2020
It is a known fact that on the daily basis significant amount of information is produced due to large number of people being connected to social networking sites. Online interaction is now included in our lifestyle whether it is through a tweet, a message or through commenting on each other posts on different platforms. Online interaction contributes a
Jayant Singh, Kishorjit Nongmeikapam
openaire   +1 more source