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.
|Tags||fuzzy machine learning decision tree fuzzy logic Scientific/Engineering Artificial Intelligence Mathematics|
|Operating Systems||Linux Windows|
|Implementation||Ada 2005 GNADE ODBC GTK+ GtkAda SQLite|
Release Notes: The database persistence layer over ODBC has been moved from GNADE ODBC, which lacks support, to native ODBC bindings from Simple Components.
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.
Release Notes: This release provides minor bugfixes and is the first release packaged for Fedora and Debian.