Functions for dimensionality reduction using principal component analysis.
Functions written by Eleni Christoforidou in MATLAB R2022b.
compute_feature_dimensions: This function computes the number of feature dimensions N needed to represent at least 99.9% of the variance in the feature set of the humanactivity dataset (built-in MATLAB dataset) using the 'pca' function.
plotEllipsoidFit: This function creates a scatter plot of the first 2 dimensions of the PCA linear vector space, and displays a contour representing the boundary, in the first two dimensions, of the the PCA ellipsoid with 2 standard deviations width.