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easily bult LDA Topic Models with just a list of docs (e.g. a list of twitter posts in CSV/TXT

Project description

PyPI version

easyLDA is a library that easily build LDA Topic Models with just a list of docs (e.g. a list of twitter posts in CSV/TXT)

github: https://github.com/shichaoji/easyLDA

  • If you have a collection of documents, and what to explore the relationship & topics of the docs, easyLDA is a very handy library to use. Simply run the commend and you’ll get a trained LDA model with results visualized

The library pipeline text preprocessing, such as tf-idf, n-grams from Gensim library

Credit to:

https://radimrehurek.com/gensim/

http://pyldavis.readthedocs.io/en/latest/readme.html

installation

$ pip install easyLDA

usage example

simple need a text file (.csv) with each row represents a document (a post, comment, short article etc.), with only one column which is the text

text file (csv) sample view

Demo 1

easy to use, just in a shell window, type: easyLDA, then specify the location of the text document

1. then choose how many topics you want the model to fit

2. choose the topic contains only single word (1) or can be phases (2/3) as well

the program will be starting to train

  • in shell $ easyLDA
Demo 2

model result

models folder created by program contains the trained model

xx.html file is the interactive visulization of the model result

Demo 3

static pic result

Demo 4

Project details


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