Metadata-Version: 2.1
Name: deeSOM
Version: 0.1.2
Summary: Deep ensemble-elastic self-organized map (deesom): a SOM based classifier to deal with large and highly imbalanced data.
Home-page: https://github.com/lbugnon/deesom
Author: L.A. Bugnon, C. Yones, D. Milone, G. Stegmayer
Author-email: lbugnon@sinc.unl.edu.ar
License: UNKNOWN
Download-URL: https://github.com/lbugnon/deeSOM/archive/0.1.2.tar.gz
Description: DeeSOM  
        --------------------------------------------------------------------------------
        Self-organized map based classifier, developed to deal with large and highly imbalanced data.
        
        sinc(i) - http://sinc.unl.edu.ar
        
        The methods automatically build several layers of SOM. Data is clustered and samples that
        are not likely to be positive class member are discarded at each level.  
        
        The elastic-deepSOM (elasticSOM) is a deep architecture of SOM layers where the map
        size is automatically set in each layer according to the data filtered in each previous 
        map. The ensemble-elasticSOM (eeSOM) uses several SOMs in ensemble layers to
        face the high imbalance challenges. These new models are particularly suited
        to handle problems where there is a labeled class of interest (positive
        class) that is significantly under-represented with respect to a higher number
        of unlabeled data.
        
        This code can be used, modified or distributed for academic purposes under GNU
        GPL. Please feel free to contact with any issue, comment or suggestion.
        
        This code was used in:
        
        "Deep neural architectures for highly imbalanced data in bioinformatics"
        L. A. Bugnon, C. Yones, D. H. Milone and G. Stegmayer*, IEEE Transactions on Neural Networks and Learning Systems,
         Special Issue on Recent Advances in Theory, Methodology and Applications of Imbalanced Learning (in press).
        
        ## Instalation
        
        ## Running the demo.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
