Skip to main content
Join the official Python Developers Survey 2018 and win valuable prizes: Start the survey!

Bayesian Hierarchical Clustering

Project description

# BHC - Bayesian Hierarchical Clustering

100:

This is a project of implementing Beyesian Hierarchical Clustering in Python.

Heller, Katherine A., and Zoubin Ghahramani. “Bayesian hierarchical clustering.” Proceedings of the 22nd international conference on Machine learning. ACM, 2005.

### Data sets: #### Data sets from the paper: toyexample: handwriting number 0,2,4. It has 64 variables, containing information of handwriting.

dim: (120, 64) <br/>

#### Data sets not in the paper: iris: This is perhaps the best known database to be found in the pattern recognition literature. Fisher’s paper is a classic in the field and is referenced frequently to this day. (See Duda & Hart, for example.) The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly separable from each other. <br/>

dim: (150, 5) <br/>

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
BHClustering-0.0.3-py2.py3-none-any.whl (5.8 kB) Copy SHA256 hash SHA256 Wheel py2.py3 May 1, 2018
BHClustering-0.0.3.tar.gz (6.0 kB) Copy SHA256 hash SHA256 Source None May 1, 2018

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page