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Results tagged with dimensionality-reduction
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user 107197
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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Factor Analysis vs Autoencoders
What is the difference between factor analysis and autoencoders.
When should we use one and not the other?
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