I would like to use NLTK (python) package within a larger graph that serves a completely different purpose (basically need to use a few tokenizers, freqdists and classifiers to clean up data to a degree first so it can then go into a processing cycle). I have read a blog post on how to incorporate python in general but it seemed to involve a lot of 3rd party elements (jython, additional Eclipse IDE for development etc) that I am not familiar with and don't want to invest a ton of time to learn new pieces (if I can help it). Ultimately one can get the info written to a flat file somewhere and turn to python to get the classification bits done and continue from there on with CloverDx as this still an adhoc process, however that feels a bit clunky and you might point me to a better way.
So my questions really are:
- does CloverDx [Designer] have any capabilities built-in that are similar to NLTK? Here I am mostly talking about predictive classifiers that one can train. Maybe I can do this all in Clover?
- If not, what's the easiest way to incorporate NLTK? Given that I also use custom corpus for this data set, ideally trying to minimise the number of resources/adjustments I need to make. I am happy to write the script on python side once and migrate across to Clover if that limits the set up steps.
- Has anyone did this (essentially supplement CloverDx with python) and package it to a degree where it can be set up in another laptop without a ton of tinkering?
Thank you for your help.