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Methods that fit nonlinear distance transformations in multidimensional scaling and trade-off the fit with structure considerations to find optimal parameters.
This is the homepage of the Structure Optimized Proximity Scaling (STOPS) project. On this page you can find links to papers, talks, data and software related to STOPS.
Except noted otherwise, content on this homepage and this work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
STOPS: Structure Optimized Proximity Scaling COPS: Cluster Optimized Proximity Scaling Assessing and Quantifying Clusteredness: The OPTICS Cordillera
| Title | Event | Date | Place |
|---|---|---|---|
| Structure Optimized Proximity Scaling (STOPS): A Framework for Hyperparameter Selection in Multidimensional Scaling | Psychoco 2017 | 09.02.2017-10.02.2017 | WU Vienna, Austria |
| COPS and STOPS: Cluster and/or Structure Optimized Proximity Scaling | Brown Bag Seminar, Institute for Statistics and Mathematics | 07.12.2016 | WU Vienna, Austria |
| The OPTICS Cordillera: Nonparametric Assessment of Clusteredness | Brown Bag Seminar, Institute for Statistics and Mathematics | 23.10.2016 | WU Vienna, Austria |
| COPS: Cluster Optimized Proximity Scaling | Psychoco 2015 | 12.02.2015-13.02.2015 | Amsterdam, The Netherlands |
| Scaling for Clusters with COPS: Cluster Optimized Proximity Scaling | CFE-ERCIM 2014 | 06.12.2014-08.12.2014 | Pisa, Italy |
The project summary page you can find here.
The most recent build is available for Windows and Linux here: STOPS Package