Co-Training Learning Algorithm
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A Co-Training Algorithm is a Semi-Supervised Learning Algorithm that can be applied where to datasets that have a natural separation of their features into two disjoint sets.
- AKA: Cotraining Algorithm.
- See: Self-Training Algorithm.
References
2004
- (Mihalcea, 2004) ⇒ Rada Mihalcea. (2004). "Co-training and Self-training for Word Sense Disambiguation." In: Proceedings of NAACL Conference (NAACL 2004).
2003
- (Strehl & Ghosh, 2003) ⇒ Alexander Strehl, and Joydeep Ghosh. (2003). "Cluster Ensembles -- A knowledge reuse framework for combining multiple partitions." In: The Journal of Machine Learning Research, (3). doi:10.1162/153244303321897735
- Cited by ~791
2000
- (Nigam & Ghani, 2000) ⇒ Kamal Nigam, and Rayid Ghani. (2000). "Analyzing the Effectiveness and Applicability of Co-training." In: Proceedings of the ninth international conference on Information and knowledge management (CIKM 2000). doi:10.1145/354756.354805
- The co-training setting [[[1998_CombiningLabAndUnlabDataCotraining|1]]] applies to datasets that have a natural separation of their features into two disjoint sets
1998
- (Blum & Mitchell, 1998) ⇒ Avrim Blum, and Tom M. Mitchell. (1998). "Combining Labeled and Unlabeled Data with Co-training." In: Proceedings of COLT 1998 Conference. doi:10.1145/279943.279962.