Andromeda: Semantic Interaction for Dimension Reduction
Andromeda enables users to directly manipulate the data points in 2D plots of high-dimensional data to explore alternative dimension reduction projections. Andromeda implements interactive weighted multidimensional scaling (WMDS) with semantic interaction. Andromeda allows for both parametric and observation-level interaction to provide in-depth data exploration. A machine learning approach enables WMDS to learn from user manipulated projections.
Try Andromeda and make your own modifications using these computational notebooks:
- Andromeda in Jupyter on GitHub and Binder.
- Andromeda JS in ObservableHQ
- Andromeda demo video
Suggested papers
Observation-Level and Parametric Interaction for High-Dimensional Data Analysis
Jessica Zeitz Self, Michelle Dowling, John Wenskovitch, Ian Crandell, Ming Wang, Leanna House, Scotland Leman, Chris North
ACM Transactions on Interactive Intelligent SystemsVolume 8Issue 2Article No.: 15pp 1–36