Semi-Supervised Classification Algorithm: Difference between revisions
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A [[Semi-Supervised Classification Algorithm]] is a [[ | A [[Semi-Supervised Classification Algorithm]] is a [[semi-supervised learning algorithm]] that is a [[data-driven classification algorithm]]. | ||
* <B | * <B>Context</U>:</B> | ||
** | ** It can range from being a [[Semi-Supervised Binary Classification Algorithm]] to being a [[Semi-Supervised Multiclass Classification Algorithm]]. | ||
** It can be implemented into a [[Semi-Supervised Classification System]] (to solve a [[semi-supervised classification task]]). | |||
** | ** … | ||
* <B | * <B>Example(s):</B> | ||
** [[Progressive Transductive Support Vector Machine]] ([[PTSVM]]). | ** [[Progressive Transductive Support Vector Machine]] ([[PTSVM]]). | ||
** A [[Semi-Supervised Named Entity Recognition Algorithm]]. | ** A [[Semi-Supervised Named Entity Recognition Algorithm]]. | ||
** [[ | ** A [[Semi-Supervised Relation Mention Recognition Algorithm]], such as [[Snowball Algorithm|Snowball]]. | ||
* <B> | ** … | ||
* <B>Counter-Example(s):</B> | |||
** a [[Fully-Supervised Classification Algorithm]]. | |||
** a [[Semi-Supervised Estimation Algorithm]], or [[Semi-Supervised Ranking Algorithm]]. | |||
* <B>See:</B> [[Self-Supervised Learning Algorithm]]. | |||
---- | ---- | ||
---- | ---- | ||
===2008=== | == References == | ||
* ([[2008_SemiSupervisedLearningLitReview|Zhu, 2008]]) | |||
=== 2008 === | |||
* ([[2008_SemiSupervisedLearningLitReview|Zhu, 2008]]) ⇒ [[Xiaojin Zhu]]. ([[2008]]). “[http://www.cs.wisc.edu/~jerryzhu/pub/ssl_survey.pdf Semi-Supervised Learning Literature Survey (revised edition)]." Technical Report 1530, Department of Computer Sciences, University of Wisconsin, Madison. | |||
===2007=== | === 2007 === | ||
* ([[2007_SemiSupervisedLearning|Zhu, 2007]]) | * ([[2007_SemiSupervisedLearning|Zhu, 2007]]) ⇒ Xiaojin Zhu. ([[2007]]). “[http://pages.cs.wisc.edu/~jerryzhu/pub/sslicml07.pdf Semi-Supervised Learning]." Tutorial at ICML 2007. | ||
===2003=== | === 2003 === | ||
* ([[ | * ([[2003_LearningwithProgressiveTransduc|Chen et al., 2003]]) ⇒ Yisong Chen, Guoping Wang, and Shihai Dong. ([[2003]]). “[http://dx.doi.org/10.1016/S0167-8655(03)00008-4 Learning with Progressive Transductive Support Vector Machine].” In: Pattern Recognition Letters, 24(12). [http://dx.doi.org/10.1016/S0167-8655(03)00008-4 doi:10.1016/S0167-8655(03)00008-4] | ||
---- | ---- | ||
__NOTOC__ | __NOTOC__ | ||
[[Category:Concept]] | [[Category:Concept]] |
Latest revision as of 20:56, 23 September 2021
A Semi-Supervised Classification Algorithm is a semi-supervised learning algorithm that is a data-driven classification algorithm.
- Context:
- It can range from being a Semi-Supervised Binary Classification Algorithm to being a Semi-Supervised Multiclass Classification Algorithm.
- It can be implemented into a Semi-Supervised Classification System (to solve a semi-supervised classification task).
- …
- Example(s):
- Counter-Example(s):
- See: Self-Supervised Learning Algorithm.
References
2008
- (Zhu, 2008) ⇒ Xiaojin Zhu. (2008). “Semi-Supervised Learning Literature Survey (revised edition)." Technical Report 1530, Department of Computer Sciences, University of Wisconsin, Madison.
2007
- (Zhu, 2007) ⇒ Xiaojin Zhu. (2007). “Semi-Supervised Learning." Tutorial at ICML 2007.
2003
- (Chen et al., 2003) ⇒ Yisong Chen, Guoping Wang, and Shihai Dong. (2003). “Learning with Progressive Transductive Support Vector Machine.” In: Pattern Recognition Letters, 24(12). doi:10.1016/S0167-8655(03)00008-4