Compared to using PCA for dimensionality reduction, using a neural autoencoder has the big advantage that it works with source data that contains both numeric and categorical data, while PCA works ...

Figure 1: Neural Autoencoder Dimensionality Reduction in Action A good way to see where this article is headed is to take a look at the screenshot of a demo program in Figure 1. The demo uses a ...