(Choose 2 answers)
Which of the following are recommended applications of PCA? Select all that apply.
A. Preventing overfitting: Reduce the number of features (in a supervised learning problem), so that there a fewer parameters to learn
B. As a replacement for (or alternative to) linear regression: For most learning applications, PCA and linear regression give substantially similar results.
C. Data compression: Reduce the dimension of your input data, which will be used in a supervised learning algorithm (i.e., use PCA so that your supervised learning algorithm runs faster).
D. Data visualization: Reduce data to 2D (or 3D) so that it can be plotted.
Eatt 9
