https://jongha-jeon-dev.github.io/standarderror/tags/pca/Recent content in Pca on The Standard ErrorHugo -- 0.123.7en-gbTue, 13 Oct 2026 00:00:00 +0000https://jongha-jeon-dev.github.io/standarderror/lectures/linear-algebra-4-equal-eigenvalues/Mon, 31 Aug 2026 00:00:00 +0000https://jongha-jeon-dev.github.io/standarderror/lectures/linear-algebra-4-equal-eigenvalues/A correlation matrix whose two largest eigenvalues differ by 0.02, where the component carrying the most variance is the one that moves 42 degrees between samples — and the resampling check reports a third of it.https://jongha-jeon-dev.github.io/standarderror/lectures/linear-algebra-7-scree-plot/Tue, 01 Sep 2026 00:00:00 +0000https://jongha-jeon-dev.github.io/standarderror/lectures/linear-algebra-7-scree-plot/Asked about a matrix of pure noise, the elbow returns 18 different answers across 300 draws and never once returns none — while three calibrated rules get it right. And the rule that is provably optimal reports zero components where three exist.https://jongha-jeon-dev.github.io/standarderror/lectures/ml-31-pca/Tue, 13 Oct 2026 00:00:00 +0000https://jongha-jeon-dev.github.io/standarderror/lectures/ml-31-pca/PCA keeps the directions along which the inputs vary most. On real data that can be a choice of units, and the direction that predicts the target can come fourth.