Cargando…
Directly Identify Unexpected Instances in the Test Set by Entropy Maximization
In real applications, a few unexpected examples unavoidably exist in the process of classification, not belonging to any known class. How to classify these unexpected ones is attracting more and more attention. However, traditional classification techniques can’t classify correctly unexpected instan...
Autores principales: | Sha, Chaofeng, Xu, Zhen, Wang, Xiaoling, Zhou, Aoying |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122406/ http://dx.doi.org/10.1007/978-3-642-00672-2_67 |
Ejemplares similares
-
Instance Sequence Queries for Video Instance Segmentation with Transformers
por: Xu, Zhujun, et al.
Publicado: (2021) -
Inverting Monotonic Nonlinearities by Entropy Maximization
por: Solé-Casals, Jordi, et al.
Publicado: (2016) -
A Direct Link between Rényi–Tsallis Entropy and Hölder’s Inequality—Yet Another Proof of Rényi–Tsallis Entropy Maximization
por: Tanaka, Hisa-Aki, et al.
Publicado: (2019) -
Instances supérieures
Publicado: (1959) -
Maximal Information Coefficient-Based Testing to Identify Epistasis in Case-Control Association Studies
por: Guo, Yingjie, et al.
Publicado: (2022)