Mapping features to principal components
Given this output of the first two principal components and assuming you were only going to use two principal components, drag each feature to the principal component the feature contributes to the most.
Rotation (n x k) = (8 x 8):
PC1 PC2 ...
bedrooms 0.3820653 0.21552040 ...
bathrooms 0.4795492 -0.02638248 ...
sqft_living 0.5147084 0.11931744 ...
sqft_above 0.4766738 -0.14246658 ...
view 0.1503091 0.34519352 ...
condition -0.1079633 0.51325217 ...
sqft_basement 0.1439464 0.53923994 ...
yr_built 0.2773924 -0.49492977 ...
Diese Übung ist Teil des Kurses
Dimensionality Reduction in R
Interaktive Übung
Setze die Theorie in einer unserer interaktiven Übungen in die Praxis um
