Metadata-Version: 1.0
Name: scw
Version: 1.0
Summary: An implementation of Exact Soft Confidence-Weighted Learning
Home-page: https://pypi.python.org/pypi/scw
Author: Ishita Takeshi
Author-email: ishitah.takeshi@gmail.com
License: MIT
Description: Exact Soft Confidence-Weighted Learning
        =======================================
        
        The explanation of the algorithm
        --------------------------------
        
        | This is an online supervised learning algorithm.
        | This learning method enjoys all the four salient properties:
        
        -  Large margin training
        -  Confidence weighting
        -  Capability to handle non-separable data
        -  Adaptive margin
        
        The paper is `here`_.
        
        There are 2 kinds of implementations presented in the paper, which
        served as
        
        ::
        
            scw.SCW1(C, ETA)
            scw.SCW2(C, ETA)
        
        in the code. C and ETA are hyperparameters.
        
        Usage
        -----
        
        ::
        
            from scw import SCW1, SCW2
        
            scw = SCW1(C=1.0, ETA=1.0)
            weights, covariance = scw.fit(training_data, teachers)
            results = scw.perdict(test_data)
        
        ``teachers`` is 1-dimensional and ``training_data`` and ``test_data``
        are 2-dimensional array.
        
        .. _here: http://icml.cc/2012/papers/86.pdf
        
Keywords: Exact Soft Confidence-Weighted Learning
Platform: UNKNOWN
