Replication Data for: Uncertainty-Aware Principal Component Analysis

The software is a JavaScript library for performing principal component analysis and dimensionality reduction on datasets consisting of multivariate probability distributions. Each plot of the image series used UA-PCA to project a dataset consisting of multivariate normal distributions.

The covariance matrices of the dataset instances were scaled with different factors resulting in different UA-PCA projections. The projected probability distributions are displayed using isolines of their probability density functions. As the scaling value increases, the projection changes, showing the sensitivity of UA-PCA to changes in variance.