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 ...
Bu egzersiz
Dimensionality Reduction in R
kursunun bir parçasıdırUygulamalı interaktif egzersiz
İnteraktif egzersizlerimizden biriyle teoriyi pratiğe dökün
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