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    Fuzzy machine learning framework

    Fuzzy machine learning framework

    A library and a GUI front-end for fuzzy machine learning

    Fuzzy machine learning framework is a library and a GUI front-end for machine learning using intuitionistic fuzzy data. The approach is based on the intuitionistic fuzzy sets and the possibility theory. Further characteristics are fuzzy features and classes; numeric, enumeration features and features based on linguistic variables; user-defined features; derived and evaluated features; classifiers as features for building hierarchical systems; automatic refinement in case of dependent features; incremental learning; fuzzy control language support; object-oriented software design with extensible objects and automatic garbage collection; generic data base support through ODBC or SQLite; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use.
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  • 2
    The Widget Set for Super-Light Applications is a minimalist GUI toolkit written in Pascal. Rendering backends include Xlib, SDL and DirectFB. Visit our trac wiki for more information and updates: http://sourceforge.net/apps/trac/wiseslap
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