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-rw-r--r--posts/2019-01-03-discriminant-analysis.md5
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diff --git a/posts/2019-01-03-discriminant-analysis.md b/posts/2019-01-03-discriminant-analysis.md
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+++ b/posts/2019-01-03-discriminant-analysis.md
@@ -176,6 +176,11 @@ 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 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`.
+
### Fisher discriminant analysis
The Fisher discriminant analysis involves finding an $n$-dimensional