What are some advanced techniques for reducing data dimensions?
An example of an AI chatbot conversation about advanced techniques for reducing data dimensions.
What are some advanced techniques for reducing data dimensions?
Some advanced techniques include PCA, t-SNE, and UMAP. Would you like to know more about any specific method?
Can you explain PCA in detail?
Principal Component Analysis (PCA) transforms data to a new coordinate system, reducing dimensions while preserving variance.
What are the advantages of using t-SNE over PCA?
t-SNE is better for visualizing high-dimensional data as it preserves local structures, making clusters more apparent.
Are there any drawbacks to using UMAP?
Yes, UMAP can be sensitive to parameter choices and may require careful tuning for optimal results.
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