Installation
About
We present 'FACT' (Feature Attributions for ClusTering), a framework for unsupervised interpretation methods that can be used with an arbitrary clustering algorithm. The package is capable of re-assigning instances to clusters (algorithm agnostic), preserves the integrity of the data and does not introduce additional models. 'FACT' is inspired by the principles of model-agnostic interpretation in supervised learning. Therefore, some of the methods presented are based on 'iml', a R Package for Interpretable Machine Learning by Christoph Molnar, Giuseppe Casalicchio, and Bernd Bischl (2018) doi:10.21105/joss.00786.
Bug report | File report |
Key Metrics
Downloads
Yesterday | 7 0% |
Last 7 days | 57 -15% |
Last 30 days | 272 -17% |
Last 90 days | 777 -2% |
Last 365 days | 2.830 +604% |