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Related Questions
- What are the key differences in the dimensionality reduction techniques PCA and t-SNE?
- How do PCA and t-SNE handle high-dimensional data?
- Can PCA preserve the local structure of the data like t-SNE?
- What are the limitations of PCA in preserving the global structure of the data?
- How does t-SNE's non-linear nature affect its ability to preserve the structural information of the data?
- Can PCA be used for visualizing high-dimensional data, and if so, what are its limitations?
- How do the parameter settings in t-SNE (e.g., perplexity, learning rate) impact its ability to preserve the structural information of the data?
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