Text Clustering

This repository contains tools to easily embed and cluster texts in the Tibetan language as well as label clusters and produce visualizations of those labeled clusters.

Install

Install the library to get started:

pip install --upgrade bocluster

Usage

The pipeline can be used following the code block below.

from datasets import load_dataset
from bocluster.cluster import BoClusterClassifier

# load a Tibetan language text dataset
ds = load_dataset('billingsmoore/LotsawaHouse-bo-en', split='train')

# initilialize a BoClusterClassifier object
bcc = BoClusterClassifier()

# fit the classifier on a set of texts
bcc.fit(ds['bo'][:1000])

# if you want to treat all data points as members of clusters, with no data treated as outliers
bcc.classify_outliers()

# show a visualization of results
bcc.show()