Dimensionality Reduction: Principal Component Analysis (PCA)
Aim
To apply Principal Component Analysis (PCA) for dimensionality reduction by transforming high-dimensional data into a lower-dimensional space while retaining the maximum variance.
To apply Principal Component Analysis (PCA) for dimensionality reduction by transforming high-dimensional data into a lower-dimensional space while retaining the maximum variance.