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
<https://github.com/numpy/numpy/issues/2434>`_, 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 0.2.0
-------------
- Changed Development Status to Alpha
- Removed Sentence2Vec as that functionality is included in current
gensim versions' Doc2Vec class
- Added Changelog
=======
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
<https://github.com/numpy/numpy/issues/2434>`_, 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 0.2.0
-------------
- Changed Development Status to Alpha
- Removed Sentence2Vec as that functionality is included in current
gensim versions' Doc2Vec class
- Added Changelog
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