Loading…
useR! 2024
Attending this event?
In Person & Virtual
8 - 11 July, 2024
Learn more and Register to Attend

The Sched app allows you to build your schedule but is not a substitute for your event registration. You must be registered for useR! 2024 to participate in the sessions. If you have not registered but would like to join us, please go to the event registration page to purchase a registration.

Please note: This schedule is automatically displayed in Central European Time (UTC+1). To see the schedule in your preferred timezone, please select from the drop-down menu to the right, above "Filter by Date." The schedule is subject to change.
Back To Schedule
Wednesday, July 10 • 15:20 - 15:40
Visualize Your Fitted Nonlinear Dimension Reduction Model in High-Dimensional Space - Jayani Piyadi Gamage, Monash University, Australia

Sign up or log in to save this to your schedule, view media, leave feedback and see who's attending!

Tweet Share
Nonlinear dimension reduction (NLDR) techniques such as tSNE, and UMAP provide a low-dimensional representation of high-dimensional data using non-linear transformation. The methods and parameter choices can create wildly different representations, making it difficult to decide which is best, or whether any or all are accurate or misleading. NLDR often exaggerates random patterns, sometimes due to the samples observed. But NLDR views have an important role in data analysis because, if done well, they provide a concise visual (and conceptual) summary of high-dimensional distributions. To help evaluate the NLDR we have developed an algorithm to show the 2D NLDR model in the high-dimensional space, viewed with a tour. One can see if the model fits everywhere or better in some subspaces, or completely mismatches the data. It is used to help with evaluating which 2D layout is the best representation of the high-dimensional distribution. Also, we can see how different methods may have similar summaries or quirks. This methodology is available in the R package `quollr`. We'll demonstrate this using single-cell data, focusing on understanding cluster structure.
Speakers
avatar for Jayani Piyadi Gamage

Jayani Piyadi Gamage

Miss., Monash University, Australia
I’m a second year PhD student in the Department of Econometrics and Business Statistics at Monash University, Australia. Under the guidance of Professor Dianne Cook, Dr. Paul Harrison, Dr. Michael Lydeamore, and Dr. Thiyanga Talagala, my research focuses on developing a novel tool... Read More →

Wednesday July 10, 2024 15:20 - 15:40 CEST
Pongau + Flachgau
  Big and high-dimensional data
Feedback form isn't open yet.