Interactive Bayesian Hierarchical Clustering
Abstract
Clustering is a powerful tool in data analysis, but it is often difficult to find a grouping that aligns with a user’s needs. To address this, several methods incorporate constraints obtained from users into clustering algorithms, but unfortunately do not apply to hierarchical clustering. We design an interactive Bayesian algorithm that incorporates user interaction into hierarchical clustering while still utilizing the geometry of the data by sampling a constrained posterior distribution over hierarchies. We also suggest several ways to intelligently query a user. The algorithm, along with the querying schemes, shows promising results on real data.
Cite
Text
Vikram and Dasgupta. "Interactive Bayesian Hierarchical Clustering." International Conference on Machine Learning, 2016.Markdown
[Vikram and Dasgupta. "Interactive Bayesian Hierarchical Clustering." International Conference on Machine Learning, 2016.](https://mlanthology.org/icml/2016/vikram2016icml-interactive/)BibTeX
@inproceedings{vikram2016icml-interactive,
title = {{Interactive Bayesian Hierarchical Clustering}},
author = {Vikram, Sharad and Dasgupta, Sanjoy},
booktitle = {International Conference on Machine Learning},
year = {2016},
pages = {2081-2090},
volume = {48},
url = {https://mlanthology.org/icml/2016/vikram2016icml-interactive/}
}