Metadata-Version: 1.1
Name: libra_py
Version: 0.0.1
Summary: Split Linearized Bregman Iteration
Home-page: https://github.com/tansey/smoothfdr
Author: Xinwei Sun
Author-email: sxwxiaoxiaohehe@pku.edu.cn
License: MIT
Description: Citing libra_py
        =============
        
        The library libra_py is an academic project. The time and resources spent developing fastFM are therefore justified 
        by the number of citations of the software. If you publish scientific articles using libra_py, please cite the following article (bibtex entry `citation.bib <http://jmlr.org/papers/v17/15-355.bib>`_).
        
            Bayer, I. "fastFM: A Library for Factorization Machines" Journal of Machine Learning Research 17, pp. 1-5 (2016)
        
        
        libra_py: A Package for sparsity problem
        ============================================
        
        
        
        Supported Operating Systems
        ---------------------------
        fastFM has a continuous integration / testing servers (Travis) for **Linux (Ubuntu 14.04 LTS)**
        and **OS X Mavericks**. Other OS are not actively supported.
        
        Usage
        -----
        .. code-block:: python
        
            from fastFM import als
            fm = als.FMRegression(n_iter=1000, init_stdev=0.1, rank=2, l2_reg_w=0.1, l2_reg_V=0.5)
            fm.fit(X_train, y_train)
            y_pred = fm.predict(X_test)
        
        
        Tutorials and other information are available `here <http://arxiv.org/abs/1505.00641>`_.
        The C code is available as `subrepository <https://github.com/ibayer/fastFM-core>`_ and provides 
        a stand alone command line interface. If you have still **questions** after reading the documentation please open a issue at GitHub.
        
        +----------------+------------------+-----------------------------+
        | Family         | Solver           | Loss                        |
        +================+==================+=============================+
        | Gaussian       | LBI_Linear       | Square Loss                 |
        +----------------+------------------+-----------------------------+
        | Binomial       | LBI_Logit        | Logit Model                 |
        +----------------+------------------+-----------------------------+
        
        *Supported solvers and tasks*
        
        Installation
        ------------
        
        **binary install**
        
        ``pip install libra_py``
        
        
        Tests
        -----
        
        
Keywords: sparsity regularization path Lasso variable-selection
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: License :: Free For Educational Use
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
