Dimensionality reduction · PCA

Interactive PCA simulator

Watch PCA reduce dimensionality step by step: centering, covariance, eigendecomposition and projection. Each step is narrated and the principal components appear as vectors on the point cloud.

simulatorPCA step by step
step 0 / 1
dataset
phase: init
state
phaseinit
n220
mean(0.21, 0.14)

Dataset with 220 points. The mean (0.21, 0.14) marks the origin from which variance will be measured. Step forward to center the data.