TWItter STock market Machine Learning package
Project description
TwistML
Disclaimer
This package is still very much under developement.
I am already seing a surprising (at least to me) number of downloads. Thank You for your interest, but please do not be disappointed, if you do not find what you are looking for, yet.
Installation
You can use pip to install TwistML like so:
$ pip install twistml
Please make you sure you have numpy and scipy installed as well. I have opted out of adding them to the install_requires for reasons described here, so it will not be installed automatically by pip.
Known Issues & Planned Improvements
Implement a DateRange class and replace all occurences of fromdate, todate, dateformat.
Implement find_files() without dateranges at all. It should be possible to simply process all files within a directory (also recursively)
TwistML currently assumes raw twitter data to be avaialble as one json file per day. Make sure the internet-archive’s file scheme is supported as well
Add support for hourly time resolution instead of daily only.
Evaluation subpackage can only deal with binary classification. Possibly explore adding multiclass.
The way logging is currently set up is weird and should be reworked.
Changes
Version 0.2.1
Added functionality for complex category subsets to tml-generate-features
Also improved documentation for tml-generate-features (on cmd line as well as docstring)
improved test coverage
Version 0.2.0
Changed Development Status to Alpha
Removed Sentence2Vec as that functionality is included in current gensim versions’ Doc2Vec class
Added Changelog
Project details
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