An Active Learning Approach with Uncertainty, Representativeness, and Diversity
Big data from the Internet of Things may create big challenge for data classification. Most active learning approaches select either uncertain or representative unlabeled instances to query their labels. Although several active learning algorithms have been proposed to combine the two criteria for q...
Saved in:
Main Authors: | Tianxu He, Shukui Zhang, Jie Xin, Pengpeng Zhao, Jian Wu, Xuefeng Xian, Chunhua Li, Zhiming Cui |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2014-01-01
|
Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2014/827586 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Anatomy Ontology Matching Using Markov Logic Networks
by: Chunhua Li, et al.
Published: (2016-01-01) -
Active Learning for Constrained Document Clustering with Uncertainty Region
by: M. A. Balafar, et al.
Published: (2020-01-01) -
Fatigue strength analysis of bogie frame in consideration of parameter uncertainty
by: Bingzhi Chen, et al.
Published: (2019-04-01) -
An Evolutionary Federated Learning Approach to Diagnose Alzheimer’s Disease Under Uncertainty
by: Nanziba Basnin, et al.
Published: (2025-01-01) -
Learning and elucidating the uncertainty in primary care by mapping uncertainty in medicine
by: Yuma Ohtsuka, et al.
Published: (2023-05-01)