Projects / Fuzzy machine learning framework

Fuzzy machine learning framework

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; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use.

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Recent releases

  •  15 Oct 2012 07:45

    Release Notes: The database persistence layer over ODBC has been moved from GNADE ODBC, which lacks support, to native ODBC bindings from Simple Components.

    •  28 May 2012 09:57

      Release Notes: This release fixes minor bugs in importing training sets from text files. The "hicolor" icon theme has been included in the binary distribution for Windows.

      •  12 Apr 2012 16:43

        Release Notes: This release provides minor bugfixes and is the first release packaged for Fedora and Debian.

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