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Machine Learning (LDA): "By finding eigenvectors we’ll find axes of new subspace where our life gets simpler: classes are more separated and data within classe
by hackandthink 4y ago
Machine Learning (LDA):
"By finding eigenvectors we’ll find axes of new subspace where our life gets simpler: classes are more separated and data within classes has lower variance."
https://medium.com/nerd-for-tech/linear-discriminant-analysis-c24d9729d3d2 https://medium.com/nerd-for-tech/linear-discriminant-analysi...
- _gmax0 4y agoAlso, if you come from a computing background, I think Eigenfaces is a great, illustrative use of eigenvalues. https://en.wikipedia.org/wiki/Eigenface https://en.wikipedia.org/wiki/Eigenface