Abstract
Information visualization is essential in making sense of large datasets. Often, high-dimensional data are visualized as a collection of points in 2D space through dimensionality reduction techniques. However, these traditional methods often don't capture the underlying structural information, clustering, and neighborhoods well. GMap is a practical algorithmic framework for visualizing relational data with geographic-like maps. This approach is effective in various domains.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
