Principal Component Analysis
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Summary
The basic principles underlying PCA, data standardization, possible visualizations of the PCA results, and outlier detection are addressed and the potential of using PCA for dimensionality reduction is illustrated on several real-world datasets.
- Type
- preprint
- Published
- 2018-04-07
- Cited by
- 373
- References
- 237
- Access
- Open access
- OpenAlex
- https://openalex.org/W2796210736
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:4717487
Keywords
Principal component analysis, Dimensionality reduction, Computer science, Principal (computer security), Data exploration
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- A data mining approach to predict forest fires using meteorological data
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- Shape Classification and Analysis: Theory and Practice
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