Supervised Dimensionality Reduction Task
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A Supervised Dimensionality Reduction Task is a Dimensionality Reduction Task that is a Supervised Learning Task.
- Context:
- It can be solved by a Supervised Dimensionality Reduction System (that implements a Supervised Dimensionality Reduction Algorithm.
- It can range from being a Supervised Space-Preserving Dimensionality Reduction Task(supervised feature selection) to being a Supervised Feature-Space Compression Task.
- It can be a preprocessing step to a Supervised Predictive Modeling Task.
- …
- Counter-Example(s):
- See: Compression.
Context
1998
- (Baker & McCallum, 1998) ⇒ L. Douglas Baker, and Andrew McCallum. (1998). “Distributional Clustering of Words for Text Classification.” In: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval. ISBN:1-58113-015-5 doi:10.1145/290941.290970
- QUOTE: ... unlike some other unsupervised dimensionality-reduction techniques, such as Latent Semantic Indexing, we are able to compress the feature space much more aggressively, while still maintaining high document classification accuracy. ... significantly better than Latent Semantic Indexing [6], class-based clustering [1], feature selection by mutual information [23] or Markov-blanket-based feature selection [13].