pyclustertend 1.3.3

A package to assess cluster tendency

pyclustertend

Presentation :

pyclustertend is a python package to do cluster tendency. Cluster tendency consist to assess if clustering algorithms are relevant for a dataset.

Three methods for assessing cluster tendency are currently implemented :

• Hopkins Statistics
• VAT
• Metric based method (silhouette, calinksi, davies bouldin)

Installation :

    pip install pyclustertend

Usage :

Example Hopkins :

    >>>from sklearn import datasets
    >>>from pyclustertend import hopkins
    >>>from sklearn.preprocessing import scale
    >>>X = scale(datasets.load_iris().data)
    >>>hopkins(X,150)
    0.18950453452838564

Example VAT :

    >>>from sklearn import datasets
    >>>from pyclustertend import vat
    >>>from sklearn.preprocessing import scale
    >>>X = scale(datasets.load_iris().data)
    >>>vat(X)

Example Metric :

    >>>from sklearn import datasets
    >>>from pyclustertend import assess_tendency_by_metrics
    >>>from sklearn.preprocessing import scale
    >>>X = scale(datasets.load_iris().data)
    >>>assess_tendency_by_metrics(X)
    2.0