It maps high-dimensional data into a lower-dimensional space while retaining the structure of the original data. t-SNE is often used for visualizing high-dimensional data and clustering analysis ...

This paper visualizes the entire quantitative investment strategies (QIS) universe in a risk-premia-segmented two-dimensional space.We propose and implement a dimensionality reduction model, for a ...

Normalizing and Encoding Source Data for an Autoencoder In practice, preparing the source data for an autoencoder is the most time-consuming part of the dimensionality reduction process. To normalize ...