Metadata-Version: 1.1
Name: twistml
Version: 0.1.25
Summary: TWItter STock market Machine Learning package
Home-page: https://bitbucket.org/madmat3001/twistml.git
Author: Matthias Manhertz
Author-email: m@nhertz.de
License: MIT
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.
Keywords: twitter stock market machine learning
Platform: any
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
