Metadata-Version: 2.1
Name: scikit-mlm
Version: 0.0.3
Summary: Minimal Learning Machine implementation using the scikit-learn API
Home-page: https://github.com/omadson/scikit-mlm
Author: Madson Dias
Author-email: madsonddias@gmail.com
License: BSD
Description: # scikit-mlm
        scikit-mlm is a Python module implementing the [Minimal Learning Machine][1] (MLM) machine learning technique using the [scikit-learn][2] API.
        
        ## quickstart
        With NumPy, SciPy and scikit-learn available in your environment, install with:
        ```
        pip3 install scikit-mlm
        ```
        
        Classification example with the nearest neighbor MLM classifier:
        ```Python
        from skmlm import NN_MLM
        from sklearn.preprocessing import MinMaxScaler
        from sklearn.model_selection import cross_val_score
        from sklearn.pipeline import make_pipeline
        from sklearn.datasets import load_iris
        
        # load dataset
        dataset = load_iris()
        
        clf = make_pipeline(MinMaxScaler(), NN_MLM(rp_number=20))
        scores = cross_val_score(clf, dataset.data, dataset.target, cv=10, scoring='accuracy')
        
        print('AVG = %.3f, STD = %.3f' % (scores.mean(), scores.std()))
        ```
        
        ## implemented methods
        ### original proposal
         - [regression (MLMR)](https://doi.org/10.1016/j.neucom.2014.11.073)
         - [classification (MLMC)](https://doi.org/10.1016/j.neucom.2014.11.073)
        
        ### speed up
         - [nearest neighbor MLM (NN_MLM)](https://link.springer.com/article/10.1007%2Fs11063-017-9587-5#Sec9)
        
        ### reference points selection methods
        #### classification
         - [opposite neighborhood MLM (ON_MLM)](https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2018-198.pdf)
        
        <!-- #### regression
         - [ ] [regularized M-FOCUSS MLM (RMF_MLM)]() -->
        
        ### cost Sensitive
         - [weighted MLM (w_MLM)](https://doi.org/10.1007/978-3-319-26532-2_61)
        
        ## how to cite scikit-mlm
        if you use scikit-mlm in your paper, please cite
        ```
        @misc{scikit-mlm,
            author       = "Madson Luiz Dantas Dias",
            year         = "2019",
            title        = "scikit-mlm: A implementation of {MLM} for scikit framework",
            url          = "https://github.com/omadson/scikit-mlm",
            institution  = "Federal University of Cear\'{a}, Department of Computer Science" 
        }
        ```
        
        ## contributors
         - [Madson Dias](https://github.com/omadson)
        
        ## acknowledgement
         - thanks for [@JamesRitchie](https://github.com/JamesRitchie), the initial idea of this project is inspired on the [scikit-rvm](https://github.com/JamesRitchie/scikit-rvm) repo
        
        
        [1]: https://doi.org/10.1016/j.neucom.2014.11.073
        [2]: http://scikit-learn.org/
        [3]: https://doi.org/10.1007/s11063-017-9587-5#
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.5
Description-Content-Type: text/markdown
