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        "author": "Isma\u00ebl Lachheb",
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        "description": "# pyclustertend [![Build Status](https://travis-ci.com/lachhebo/pyclustertend.svg?branch=master)](https://travis-ci.com/lachhebo/pyclustertend)  [![PyPi Status](https://img.shields.io/pypi/v/pyclustertend.svg?color=brightgreen)](https://pypi.org/project/pyclustertend/) [![Documentation Status](https://readthedocs.org/projects/pyclustertend/badge/?version=master)](https://pyclustertend.readthedocs.io/en/master/) [![Downloads](https://pepy.tech/badge/pyclustertend)](https://pepy.tech/project/pyclustertend) [![codecov](https://codecov.io/gh/lachhebo/pyclustertend/branch/master/graph/badge.svg)](https://codecov.io/gh/lachhebo/pyclustertend)\n\n\n\n\n## Presentation : \n\npyclustertend is a python package to do cluster tendency. Cluster tendency consist to assess if clustering algorithms are relevant for a dataset.\n\n\nThree methods for assessing cluster tendency are currently implemented  :\n\n- [x] Hopkins Statistics \n- [x] VAT\n- [x] iVAT\n- [x] Metric based method (silhouette, calinksi, davies bouldin)\n\n## Installation : \n\n```shell\n    pip install pyclustertend\n```\n\n## Usage : \n\n### Example Hopkins : \n\n```python\n    >>>from sklearn import datasets\n    >>>from pyclustertend import hopkins\n    >>>from sklearn.preprocessing import scale\n    >>>X = scale(datasets.load_iris().data)\n    >>>hopkins(X,150)\n    0.18950453452838564\n```\n\n### Example VAT :\n\n```python\n    >>>from sklearn import datasets\n    >>>from pyclustertend import vat\n    >>>from sklearn.preprocessing import scale\n    >>>X = scale(datasets.load_iris().data)\n    >>>vat(X)\n```\n\n<img height=\"350\" src=\"https://raw.githubusercontent.com/lachhebo/pyclustertend/screenshots/vat.png\" />\n\n\n### Example Metric : \n\n\n```python\n    >>>from sklearn import datasets\n    >>>from pyclustertend import assess_tendency_by_metrics\n    >>>from sklearn.preprocessing import scale\n    >>>X = scale(datasets.load_iris().data)\n    >>>assess_tendency_by_metrics(X)\n    2.0\n```\n\n\n",
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