Skip to main content

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.

Source Distribution

BHClustering-0.0.2.tar.gz (6.0 kB view hashes)

Uploaded source

Built Distribution

BHClustering-0.0.2-py2.py3-none-any.whl (5.8 kB view hashes)

Uploaded py2 py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page