22 Exercise (part 1, Updated Nov 10) How would you calculate efficiently the PCA of data where the dimensionality d is much larger than the number of
{"Image DocumentName": "Exercise (part 1, Updated Nov 10)", "Image ImageDescription": "How would you calculate efficiently the PCA of data where the dimensionality d is much larger than the number of vector observations n? Download the Wisconsin Data from the UC Irvine repository, extract PCAs from the data, test scatter plots of original data and after projecting onto the principal components, plot Eigen values. (c) Tralvex Yeap. All Rights Reserved.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}