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Results tagged with dimensionality-reduction
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user 13947
Techniques for reducing a large number of variables or dimensions spanned by data to a smaller number of dimensions while preserving as much information about the data as possible. Prominent methods include PCA, Factor Analysis, MDS, Independent Component Analysis, Multiple Correspondence Analysis, Isomap, etc. The two main subclasses of techniques: feature extraction and feature selection.
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How does t-SNE slow down with increasing number of dimensions?
I'm trying to understand the computational bounds of t-SNE. It's learned with SGD, so it'll have to go through some number of gradient-descent iterations. We can ignore that here, and focus on the t …
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