Metadata-Version: 1.1
Name: twistml
Version: 0.2.2
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. 
        
        At this point most of the intended functionality is in place, but
        documentation is still very spotty.
        
        Installation
        ------------
        You can use pip to install TwistML like so::
        
        	$ pip install twistml
        
        Please make you sure you **have numpy, scipy and gensim installed** as
        well. I have opted out of adding them to the install_requires as this
        has caused problems in my own tests on windows machines. (For numpy the
        problem is described `here
        <https://github.com/numpy/numpy/issues/2434>`_.) So these packages 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.
        
        - gensim's LabeledSentence is deprecated, use TaggedDocument instead
        Changes
        =======
        
        Version 0.2.2
        
        - Added sentiment features based on TextBlob sentiments
        
        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
        
        
Keywords: twitter stock market machine learning
Platform: any
Classifier: Development Status :: 3 - 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
