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| -rw-r--r-- | posts/2019-01-03-discriminant-analysis.md | 3 |
1 files changed, 1 insertions, 2 deletions
diff --git a/posts/2019-01-03-discriminant-analysis.md b/posts/2019-01-03-discriminant-analysis.md index d2aaaa3..28c53d5 100644 --- a/posts/2019-01-03-discriminant-analysis.md +++ b/posts/2019-01-03-discriminant-analysis.md @@ -176,8 +176,7 @@ will result in a lossy compression / regularisation equivalent to doing analysis](https://en.wikipedia.org/wiki/Principal_component_analysis) on $(M - \bar x) V_x D_x^{-1}$. -Note that as of 2019-01-04, in the scikit-learn implementation, the prediction of -LDA is done without +Note that as of 2019-01-04, in the [scikit-learn implementation of LDA](https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/discriminant_analysis.py), the prediction is done without any lossy compression, even if the parameter `n_components` is set to be smaller than dimension of the affine space spanned by the centroids. In other words, the prediction does not change regardless of `n_components`. |