StackedML
Practice
Labs
Questions
Models
Pricing
Sign in
Practice
/
Unsupervised Learning
/
Dimensionality Reduction
/
PCA
PCA
Principal Component Analysis.
0/8
completed
1
2
3
4
5
6
7
8
easy
Principal Components Definition
2/8
What are the principal components in PCA?
A
The directions of minimum variance in the data that are orthogonal to the decision boundary
B
The cluster centroids found by K-means in the reduced-dimensional feature space
C
The columns of the original feature matrix after standardization and mean-centering
D
The eigenvectors of the covariance matrix of the data, ordered by their eigenvalues
Sign in to verify your answer