Cargando…
Active Learning for Node Classification: An Evaluation
Current breakthroughs in the field of machine learning are fueled by the deployment of deep neural network models. Deep neural networks models are notorious for their dependence on large amounts of labeled data for training them. Active learning is being used as a solution to train classification mo...
Autores principales: | Madhawa, Kaushalya, Murata, Tsuyoshi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597335/ https://www.ncbi.nlm.nih.gov/pubmed/33286933 http://dx.doi.org/10.3390/e22101164 |
Ejemplares similares
-
Evaluation of Four Lymph Node Classifications for the Prediction of Survival in Hilar Cholangiocarcinoma
por: Liu, Zhi-Peng, et al.
Publicado: (2022) -
Scalably Using Node Attributes and Graph Structure for Node Classification †
por: Merchant, Arpit, et al.
Publicado: (2022) -
Different Machine Learning and Deep Learning Methods for the Classification of Colorectal Cancer Lymph Node Metastasis Images
por: Li, Jin, et al.
Publicado: (2021) -
Self-Supervised Node Classification with Strategy and Actively Selected Labeled Set
por: Kang, Yi, et al.
Publicado: (2022) -
Mobility Classification of LoRaWAN Nodes Using Machine Learning at Network Level
por: Vangelista, Lorenzo, et al.
Publicado: (2023)