The relaibility map to visualize the distortion measured by Steadiness & Cohesiveness
Steadiness & Cohesiveness · Paper · Contact

The Reliablity Map

Overview

Okay - you measured the quality of multidimensional projections (MDP) with Steadiness & Cohesiveness. However, only quantitative metrics cannot intuitively explain how and where distortions occurred in the projection. For further analysis and practical use of the metrics, we need to visualize the occurrence of distortion. We designed The reliability map for such a purpose.

The reliability map visualizes two aspects of MDP distortions: False Groups and Missing Groups. False Groups distortion denotes where a low-dimensional group in a single cluster consists of separated groups in the original space. Missing Groups distortion occurs when the original group misses its subgroups, and therefore is divided into many separated subgroups in the projected space. Steadiness and Cohesiveness evaluate how well projections avoid False and Missing Groups, respectively.

Functionalities

The reliability map assigns purple to the area with False Groups distortion and does green to the edges with Missing Groups distortions. Moreover, the area with no distortion is represented as white, while the black area denotes the area with both distortions. Note that the color scheme is originated from Checkviz visualization.

Fig 1. The reliability maps that visualize the inter-cluster distortion of t-SNE projections (σ = [1,10,100,1,000]) made for Fashion-MNIST test dataset.

Fig 2. The UMAP, Isomap, and LLE projections of MNIST test dataset and the reliability maps that visualize each projection’s inter-cluster distortion.

The reliability map also provides the interaction to analyze Missing Groups distortions in detail. By constructing a lasso with simple mouse click interaction, you can see where the "missed groups" of selected area is located.

How to use the reliability map

The reliability map is implemented using React framework and D3.js, and served as npm project. To use it, clone this project and inject a distortion info file generated while measuring Steadiness & Cohesiveness.

git clone https://github.com/hj-n/snc-reliability-map
cd snc-reliability-map

## after injecting files and adjusting parameters
npm i 
npm start

Setup

By calling SNC.vis_info(file_path) method after computing Steadiness & Cohesiveness (please refer to the API), a json file with distortion infos are saved in designated file_path. Copy & paste the files to snc-reliability-map/src/json/ and set required arguments to run the program.

API

The reliability map is served as React component embedded in a React web application. Change the props for the component!!

<ReliabilityMap
  identifier="identifier"
  isLabel= {false}
  showMissing={true}
  showFalse={true}
  drawEdge={true}
  radius={radius} 
  stroke={stroke}
/>

• identifier : string
  • the identifier of distortion info files (set by Steadiness & Cohesiveness).
  • if the name of file is abs.json, identifier should be abs.
• isLabel : bool
  • if true and there exists a file holds the label (class) information, the reliability map also visualizes the label info by encoding color to each point.
• showMissing, showFalse : bool
  • if true, visualizes Missing / False distortions, respectively.
• drawEdge : bool
  • determines whether to display edges that encode distortion
• radius, stroke : float
  • set the radius of data points / the stroke width of edges

References / Citation

If you have used Steadiness & Cohesvieness and the reliability map for your project and wish to reference it, please cite our TVCG paper.

H. Jeon, H.-K. Ko, Y. Kim, J. Jo, and J. Seo, “Measuring and explaining the inter-cluster reliability of multidimensional projections,” IEEE Transactions on Visualization and Computer Graphics (TVCG, Proc. VIS), 2021. to appear.

Bibtex

@article{jeon21tvcg,
  author={Jeon, Hyeon and Ko, Hyung-Kwon and Kim, Youngtaek and Jo, Jaemin and Seo, Jinwook},
  journal={IEEE Transactions on Visualization and Computer Graphics (TVCG, Proc. VIS)}, 
  title={Measuring and Explaining the Inter-Cluster Reliability of Multidimensional Projections}, 
  year={2021},
  note={to appear.}
}

Contributors

Hyeon Jeon, Hyung-Kwon Ko, Jaemin Jo, Youngtaek Kim, and Jinwook Seo.

This software is mainly developed / maintained by Human-computer Interaction Laboratory @ Seoul National University.

Contact

If you are interested in using the reliability map in you project, feel free to contact!! ([email protected])