Emlens

Embedding is a potent to tool for generating a vector representation of words and networks. To fully leverage its utility, the embedding space needs to be high dimensional. While computers have no problem in understanding high dimensional space, our brains do not. This emlens aims to fill the gap by providing a set of tools for visualizing the embedding space, quantifying correlation to metadata, and calculating densities.

This package is under active development. If you have issues and feature requests, please raise them through Github.

Contents:

• emlens
  • emlens package

Install

See project page

Example

• airport networks

Indices and tables

• Index

• Module Index

• Search Page